Systems and methods for filtering media content based on user perspective

ABSTRACT

Systems and methods are provided to process a digital photo and other media. An apparatus to process digital photos can include a tangibly embodied computer processor (CP) and a tangibly embodied database. The CP can perform processing including: (a) inputting a photo from a user device, and the photo including geographic data that represents a photo location at which the photo was generated; (b) comparing at least one area with the photo location and associating an area identifier to the photo as part of photo data; and (c) performing processing based on the area identifier and the photo data. Processing can provide for (a) processing media with geographical segmentation; (b) processing media in a geographical area, based on media density; (c) crowd based censorship of media; and (d) filtering media content based on user perspective, that can be for comparison, validation and voting, for example.

RELATED APPLICATIONS AND PRIORITY

This application claims priority to and is a continuation patentapplication of U.S. patent application Ser. No. 17/200,753 filed Mar.12, 2021. Such U.S. patent application Ser. No. 17/200,753 is acontinuation-in-part (CIP) patent application of U.S. patent applicationSer. No. 17/105,054 filed on Nov. 25, 2020, which claims priority toU.S. Provisional Patent Application Ser. No. 62/940,415 filed Nov. 26,2019, the disclosures of which are all hereby incorporated by referencein their entireties. The disclosure of U.S. patent application Ser. No.17/200,753 is hereby incorporated by reference in its entirety.

BACKGROUND OF THE DISCLOSURE

Systems and methods described herein relate to processing photos andother media, and in particular to processing photos and other media in ageographical area.

Photography is popular with a wide variety of people. Photography caninclude taking pictures of points of interest, activities of interest,“selfies”, and innumerable other items. Photography can include taking apicture with a camera or other device that is dedicated to photography.Photography can include taking a picture with a smart phone, cell phone,or other user device that provides picture taking abilities as well asvarious other abilities and uses. Websites and other electronicresources exist that provide the ability to upload or otherwise savepictures that have been taken by a person. Such websites can allow auser to access pictures and perform other manipulation of pictures.However, known technology is lacking in capabilities that suchtechnology provides. The systems and methods of the disclosure addressshortcomings that exist with known technology.

SUMMARY OF THE DISCLOSURE

Systems and methods are provided to process digital photos and othermedia. An apparatus to process digital photos and other media (and forprocessing digital photos and other media) can include a tangiblyembodied computer processor (CP) and a tangibly embodied database. TheCP can perform processing including: (a) inputting a photo from a userdevice, and the photo including geographic data that represents a photolocation at which the photo was generated; (b) comparing at least onearea with the photo location and associating an area identifier to thephoto as part of photo data; and (c) performing processing based on thearea identifier and the photo data. Processing of a photo and/or acollection of photos can include area segmentation, photo deliveryprocessing including processing based on photo density, censorshipprocessing, and processing using filters. Various other features aredescribed below.

Accordingly, systems and methods of the disclosure can provide for (a)processing media with geographical segmentation; (b) media deliveryprocessing based on photo density and voter preference (c) crowd basedcensorship of media; and (d) filtering media content based on userperspective, that can be for editing, viewing, comparison, validationand voting, for example. For example, the systems and methods of thedisclosure can provide for processing media in a geographical area basedon media density. The systems and methods of the disclosure can providefor photo delivery processing including or based on photo density, votepreference, voter preference, or voting preference. Photo deliveryprocessing can be based on photo density with photo density registeringvoter preference. Various additional features are described herein.

BRIEF DESCRIPTION OF THE DRAWINGS

The disclosed subject matter of the present application will now bedescribed in more detail with reference to exemplary embodiments of theapparatus and method, given by way of example, and with reference to theaccompanying drawings, in which:

FIG. 1 is a diagram showing a photo ecosystem or ecosystem in accordancewith at least one embodiment of the disclosed subject matter.

FIG. 2 is a high level flowchart illustrating processing that can beperformed by the photo system (PS), in accordance with principles of thedisclosed subject matter.

FIG. 3 is a flowchart showing further details of area segmentationprocessing, in accordance with principles of the disclosed subjectmatter.

FIG. 4 is a flowchart showing details of “processing is performed toassign area identifier and identify boundaries of the area” inaccordance with principles of the disclosed subject matter.

FIG. 5 is a diagram showing segmentation of a remote segmentation area,in accordance with principles of the disclosed subject matter.

FIG. 6 is a flowchart showing details of the “photo system performsphoto input processing”, in accordance with principles of the disclosedsubject matter.

FIG. 7 is a flowchart showing further details of the system “processescurrent photo so as to integrate such photo into the system” inaccordance with principles of the disclosed subject matter.

FIG. 8 is a flowchart showing processing “to place a photo into avirtual container,” in accordance with principles of the disclosedsubject matter.

FIG. 9 is a flowchart showing further details of the “system performsspot generation processing”, in accordance with principles of thedisclosed subject matter.

FIG. 10 is a flowchart showing in further detail the “system watches foran event to be observed that invokes spot generation processing” inaccordance with principles of the disclosed subject matter.

FIG. 11 is a flowchart showing further details of a “spot generationprocessing” subroutine, in accordance with principles of the disclosedsubject matter.

FIG. 12 is a flowchart showing in further detail the system performs“type tagging” for a current patch, in accordance with principles of thedisclosed subject matter.

FIG. 13 is a flowchart showing further details of the system performs“type tagging” for a current spot for a type-A photo, in accordance withat least one embodiment of the disclosed subject matter.

FIG. 14 is a flowchart showing in further detail the system performs“user engagement processing,” invoked or called upon from FIG. 2, inaccordance with principles of the disclosed subject matter.

FIG. 15 is a flowchart showing in further detail the photo system“interfaces with a user device to input a new photo”, in accordance withprinciples of the disclosed subject matter.

FIG. 16 is a flowchart showing in further detail the “photo systeminterfaces with a user to input attributes of a photo” in accordancewith principles of the disclosed subject matter.

FIG. 17 is a flowchart showing in further detail the “photo systeminterfaces with a user device to perform photo user processing, inaccordance with principles of the disclosed subject matter.

FIG. 18 is a diagram that includes a GUI (graphical user interface) thatillustrates aspects of “photo info” or “photo information” processing,in accordance with principles of the disclosed subject matter.

FIG. 19 is a diagram that includes a GUI that can be presented to a useror potential user in conjunction with the user signing on or logginginto photo system, in accordance with principles of the disclosedsubject matter.

FIG. 20 is a diagram that includes a GUI 2000 that can be utilized so asto launch or invoke processing in accordance with principles of thedisclosed subject matter.

FIG. 21 is a diagram that includes a GUI 2100 that can be utilized so asto interface with the user so as to input selection of search filters,in accordance with principles of the disclosed subject matter.

FIG. 22 is a diagram that includes a GUI 2200 that can be utilized toprovide the user “spots around me” functionality in accordance withprinciples of the disclosed subject matter.

FIG. 23 is a diagram that includes a GUI 2300 that can be utilized toprovide the user information regarding a “site”, with such siteincluding a plurality of spots, in accordance with principles of thedisclosed subject matter.

FIG. 24 is a diagram that includes a GUI 2400 that illustrates “spotsaround me” functionality, in accordance with principles of the disclosedsubject matter.

FIG. 25 is a diagram that includes a GUI 2500 that can be presented tothe user to provide additional information to the user regarding spotsaround the user or user device, in accordance with principles of thedisclosed subject matter.

FIG. 26 is a diagram that includes a GUI 2600 that shows further detailsof “spots around me” functionality in accordance with principles of thedisclosed subject matter.

FIG. 27 is a diagram that includes a GUI 2700 that can be presented tothe user to provide various menu selection items in accordance withprinciples of the disclosed subject matter.

FIG. 28 is a diagram that includes a GUI 2800 that can provide variousinformation regarding one or more spots, in accordance with principlesof the disclosed subject matter.

FIG. 29 is a diagram that includes a GUI 2900 that can provide taggingof photos or allowing users to identify additional content that can beadded to or associated with a photo, for example, for future searchoptions in accordance with principles of the disclosed subject matter.

FIG. 30 is a diagram that includes a GUI 3000 that can be displayed as aresult of the user tapping or selecting a suitable button for furthertagging of photos or allowing users to identify additional content thatcan be added to or associated with a photo, for example, in accordancewith principles of the disclosed subject matter.

FIG. 31 is a diagram that includes a GUI 3100 for further tagging ofphotos or allowing users to identify additional content, which can beadded to or associated with a photo, that can be generated by the photosystem and presented to the user, in accordance with principles of thedisclosed subject matter.

FIG. 32 is a diagram that includes a GUI 3200 for further tagging ofphotos or allowing users to identify additional content, which can beadded to or associated with a photo, that can be generated by the photosystem and presented to the user, in accordance with principles of thedisclosed subject matter.

FIG. 33 is a diagram that includes a GUI 3300 for further tagging ofphotos or allow users to identify additional content, which can be addedto or associated with a photo, that can be generated by the photo systemand presented to the user, in accordance with principles of thedisclosed subject matter.

FIG. 34 is a high level flowchart showing additional processing of thedisclosure in accordance, with principles of the disclosed subjectmatter.

FIG. 35 is a flowchart showing details of “processing is performed toassign area identifier and identify boundaries of an area” of step 3500of FIG. 34, in accordance with principles of the disclosed subjectmatter.

FIG. 36 a flowchart showing details of “CP associates photo to a patch”of subroutine 3600 as called from FIG. 34, in accordance with principlesof the disclosed subject matter.

FIG. 37 is a diagram showing aspects of unique area identifier (UAI)generation, in accordance with principles of the disclosed subjectmatter.

FIG. 38 is a further diagram showing further aspects of UAI generation,in accordance with principles of the disclosed subject matter.

FIG. 39 is a flowchart showing “processor processes user request fordisplay of “visual area” on user device (cell phone)” of subroutine3900, in accordance with principles of the disclosed subject matter.

FIG. 40 is a flowchart showing “processor determines the level that thevisual area (VA) is currently displaying” of subroutine 4000, as calledfrom the processing of FIG. 39, in accordance with principles of thedisclosed subject matter.

FIG. 41 is a flowchart showing “processor, based on the coordinates ofthe Viewport Area (VA), determines search bound coordinates” ofsubroutine 4100 as called from the processing of FIG. 39, in accordancewith principles of the disclosed subject matter.

FIG. 42 is a flowchart showing “processor performs pin placementprocessing for the current viewport area that is being displayed on theuser device” of subroutine 4200 as called from the processing of FIG.39.

FIG. 43 is a flowchart showing “processor performs pin placementprocessing for area” of subroutine 4300, as called upon from theprocessing of FIG. 42, in accordance with principles of the disclosedsubject matter.

FIG. 44 is a schematic diagram also showing features of pin placementprocessing, in accordance with principles of the disclosed subjectmatter.

FIG. 45 is a schematic diagram showing further aspects of pinprocessing, in accordance with principles of the disclosed subjectmatter.

FIG. 46 is a schematic diagram showing further aspects of pinprocessing, in accordance with principles of the disclosed subjectmatter.

FIG. 47 is a schematic diagram showing yet further aspects of pinprocessing in conjunction with manipulation of thumbnails, in accordancewith principles of the disclosed subject matter.

FIG. 48 is a flowchart showing details of a processor of the disclosureperforming censorship processing, in accordance with principles of thedisclosed subject matter.

FIG. 49 is a flowchart showing “processor performs ratificationprocessing” of subroutine 4900, in accordance with principles of thedisclosed subject matter.

FIG. 50 is a flowchart showing “processor performs accumulatedratification processing” of subroutine 5000 as invoked from FIG. 49, inaccordance with principles of the disclosed subject matter.

FIG. 51 is a diagram showing aspects of censorship power rating (CPR)and required ratification number (RRN), in accordance with principles ofthe disclosed subject matter.

FIG. 52 is a schematic diagram of a user device with GUI, in accordancewith principles of the disclosed subject matter.

FIG. 53 is a schematic diagram showing a user device 5300 with the GUI5330, in accordance with principles of the disclosed subject matter.

FIG. 54 is a flowchart showing processing that can be used inconjunction with the GUI 5330 of FIG. 53, in accordance with principlesof the disclosed subject matter.

FIG. 55 is a flowchart showing filtered following processing, inaccordance with principles of the disclosed subject matter.

FIG. 56 is a flowchart showing details of subroutine 5600 as called fromFIG. 55, in accordance with principles of the disclosed subject matter.

FIG. 57 is a flowchart showing details of “CP establishes filteredfollowing (FF) association based on photos that were “taken” by thefirst user” of subroutine 5700 as called from FIG. 56, in accordancewith principles of the disclosed subject matter.

FIG. 58 is a flowchart showing details of “CP establishes filteredfollowing (FF) association based on photos that were “liked” by thefirst user” of subroutine 5800 as called from FIG. 56, in accordancewith principles of the disclosed subject matter.

FIG. 59 is a flowchart showing details of “CP establishes filteredfollowing (FF) association based on photos that were “tagged” in aparticular manner by the first user” of subroutine 5900 as called fromFIG. 56, in accordance with principles of the disclosed subject matter.

FIG. 60 is a flowchart showing details of “CP interfaces with a thirduser to allow the third user to (A) select the first user, so as to viewthe first filtered photo set, (B) select the second user, so as to viewthe second filtered photo set, AND (C) perform processing to compare thetwo photo sets” of subroutine 6000 as called from FIG. 55, in accordancewith principles of the disclosed subject matter.

FIG. 61 is a flowchart showing details of “CP interfaces with a thirduser to allow the third user to select the first user and to selectfiltered following (FF) association(s), so as to view the first filteredphoto set” of subroutine 6100 as called from FIG. 60, in accordance withprinciples of the disclosed subject matter.

FIG. 62 is a flowchart showing details of “processor performs processingto compare two filtered photo sets, and to generate results of thecomparison to be output to the third user” of subroutine 6100 as calledfrom FIG. 60, in accordance with principles of the disclosed subjectmatter.

FIG. 63 is a diagram that shows a user device 6300 displaying a GUI6330, in accordance with principles of the disclosed subject matter.

FIG. 64 is a schematic diagram showing data content 123C, in accordancewith principles of the disclosed subject matter.

FIG. 65 is a diagram further illustrating segmentation of an area 6500,in accordance with principles of the disclosed subject matter. FIG. 36 aflowchart showing details of “CP associates photo to a patch” ofsubroutine 3600 as called from FIG. 34, in accordance with principles ofthe disclosed subject matter.

FIG. 66 is a flowchart showing details of “area fill-in processing isperformed” of subroutine 6600 as called from FIG. 36, in accordance withprinciples of the disclosed subject matter.

FIG. 67 is a representation of a GUI with filtering options, inaccordance with principles of the disclosed subject matter.

DETAILED DESCRIPTION OF EXEMPLARY EMBODIMENTS

A few inventive aspects of the disclosed embodiments are explained indetail below with reference to the various figures. Exemplaryembodiments are described to illustrate the disclosed subject matter,not to limit its scope, which is defined by the claims. Those ofordinary skill in the art will recognize a number of equivalentvariations of the various features provided in the description thatfollows.

Locations exist that are popular for a variety of reasons andcharacteristics. Locations can be popular amongst local residents ortravelers. Locations can be popular for sightseeing, taking “selfies”,taking photographs, or partaking in interesting activities. Interestingactivities can include “seeing (taking pictures), eating, drinking,shopping, and various other activities including conceptual things.Conceptual things can include ideas or referendums, for example. Aparticular location can be “popular” or locations may become “popular”as a function of time. Locations that become popular as a function oftime can be dependent on seasonal events, times of day, newsworthydevelopments that are related to such location, and trending items thatare related to the particular patient.

However, visitors, travelers, and even local residents may not always beaware of these popular locations. A popular location can be marked witha physical sign or other marker so as to notify interested persons ofthe particular location. Also, some of these popular locations areidentified on maps or in travel guides. However, such information is notalways readily available to interested travelers or other persons. Suchinformation may also become outdated. Further, signs and notificationsmay not provide information about the location that helps an interestedperson to determine appealing characteristics or other features ofinterest regarding the location.

It is one objective of the present disclosure to provide information bygraphic display on a networked computer, mobile device or otherprocessing system that a user can access to identify locations ofinterest. Such locations of interest can include popular locations. Theinformation can be used for planning purposes when a user is planning avisit to the location of interest or near the location of interest.Another objective of the present disclosure is to provide a method andsystem for processing photos that determine popularity or registers auser vote of preference; and the popularity of a location or area can beidentified by being referred to as a “spot”. Thus, an area that has apredetermined density of photos can be deemed a “spot” by the PS (photosystem) of the disclosure. Thus, for example, a “patch” (as describedbelow) that has a predetermined density of photos can be deemed a “spot”by the PS. Other types of areas, e.g. a “local” may also be deemed a“spot”. The method and system can determine the popularity of an area,for example the popularity of a patch, using various characteristics orattributes of interest, which can be associated with the area in asuitable database. Once identified as a “spot”, the database can containinformation that identifies the spot, conveys information regarding theparticular location of the spot, and includes various other attributesof the spot. It is a further objective of the present disclosure toprovide the user with photos previously captured at the spot in order toassist the user in determining if the characteristics of the spot are ofinterest. Another objective of the disclosure is to utilize usersupplied content and preferences to assist in a determination inidentification of “trusted critics” by establishing user power ratingsby area of interest. Such user power ratings can include theestablishment of user dashboards highlighting volume of activity,concentration of followers, areas of interest, and geographicalproclivity. A further objective is to provide users the ability toidentify and organize under “affinity groups.” A further objective is toprovide users the ability of “filtered following” that organizes contentbased upon user interests, preferences including trusted critics,affinity groups, geography, and other attributes. It is a furtherobjective to allow users the ability to flexibly organize and reorganizecontent and perspectives, preferences, user following and/or affinitygroups to validate or more generally perform an “assessment” of thepopularity or other attribute of a spot. It is a further objective ofthe present disclosure to provide a system that supplies popular spotcharacteristics and other information to a user that is dynamicallyupdated over time so as to be of increased relevance to the user. It isa further objective of the present disclosure to provide information tothe user regarding a spot that is specifically customized to the user.

The systems and methods of the disclosure can provide the aboveobjectives and can provide various other features as described in detailbelow. The system of the disclosure can include a computer, computersystem or machine that can be in the form of or include one or morecomputer processors “CPs” and one or more databases. The computer caninclude or be in the form of or be connected to a network server.Processing can be performed that includes accessing a photo databasecontaining photos, i.e. digital photos, and location data anddetermining one or more clusters of the digital photos based on thelocation data. Processing can further include associating time data anda variety of other data appended to the photo or cluster of photos.Processing can be performed to determine a popular spot location forrepresenting the digital photo or cluster of digital photos and togenerate results, which can be stored in a database for later access.

In at least one embodiment of the disclosure, the process of determininga popular location, herein referred to as a “spot”, can begin withgeographic segmentation of the globe or some other area. Geographicsegmentation can include the establishment of uniquely identifiableareas, which can vary in size. The largest areas can be as large as thePacific Ocean or the Antarctic. The smallest areas can be a point or anarea of a few square feet. A smallest area, of the uniquely identifiableareas, can correspond to what is herein referred to as a “patch”. A“patch” can become a “spot”, i.e. a “patch-spot” if density of photos inthe patch is sufficient. The methodology of the disclosure can initiallyestablish larger location areas that are, for example, approximately 100miles×100 miles in area. The smallest area that can be referred to as apatch, can be approximately 13 feet×13 feet. However, as describedbelow, it should be appreciated that the particular areas processed,including the size of such areas, can vary in implementation of a systemof the invention.

Geographic segmentation of an area under consideration, such as theworld or globe, can start with a desired segmentation, such as the 100mile×100 mile segmentation. Such areas that have been formed bysegmentation, can be referred to as first level areas. Each of the firstlevel areas can be divided into second level areas. Each of the secondlevel areas can further be divided into third level areas. Furthersegmentation can be provided. The particular area to be processed, be itthe world or some smaller area such as a trade show venue, can vary asdesired. Additionally, the number of levels provided can vary asdesired, as well as size of each of the areas. Accordingly, theparticular number of levels of areas, size of the areas, and otherattributes of areas as described herein are for purposes ofillustration. The number of levels of areas can be varied as desired,the size of the areas can be varied as desired, the shape of the areascan be varied as desired, other attributes of the areas can be varied asdesired, interrelationship between the areas can be varied as desired,and/or other aspects of geographic segmentation can be varied asdesired. The size and shape of the area that constitutes or includes aspot can be varied as desired. The sizes as described herein areapproximate and may well vary within thresholds. Such thresholds mayinclude variance, of the size of the areas, by + or −5%, + or −10%, + or−15%, + or −20%, for example. For example, geographic segmentation areasor areas can be generally standardized into 6 size categories, inaccordance with at least one embodiment of the disclosure. Thesegmentation areas can include 6 size categories. The 6 size categoriescan illustratively include:

(1) “Remote”: 100 miles by 100 miles (19,700 across the earth);

(2) “Territory”: 10 miles by 10 miles (1.97 Million (M) spots across theearth);

(3) “Sector”: 1 mile by 1 mile (1 spot per square (sq) mile-197 M spotsacross the earth);

(4) “Quadrant”: ¼ mile by ¼ mile (1,340 ft by 1,340 ft-16 spots persquare mile 3.15 Billion (B) across earth); and

(5) “Local”: 134 ft by 134 ft (1,600 spots per square mile-315B acrossthe earth).

(6) “Patch”: 13.4 foot by 13.4 foot areas (160,000 per square mile-31.5trillion across the earth).

Accordingly, the remote areas can constitute first level areas, theterritory areas can constitute second level areas, the sector areas canconstitute third level areas, the quadrant areas can constitute fourthlevel areas, the local areas can constitute fifth level areas, and thepatch areas can constitute sixth level areas. Accordingly, the largestof the areas can be the remote areas. The smallest of the areas can bethe patch areas. The above naming or nomenclature is used for purposesof explanation and discussion herein. It should of course be appreciatedthat the areas can be named as desired.

As described herein, the areas as defined and processed in the system ofthe disclosure can be formed by various techniques and mechanisms. Areaboundaries for each remote area, for example, can be established usinglongitude-latitude data. Various information can be used to determinethe boundaries of the remote areas and/or to determine thelongitude-latitude (long-lat) of a particular location or geographicalfeature. Such information can include natural landmass orientationboundaries, ocean or water boundaries, concentrations of populations,countries, states, provinces, counties, cities and other predefinedsites or areas.

Once the first level areas are defined with boundaries of each of the“remote” can be defined using a 100 mile×100 mile, the second levelareas (territories) can then be defined. The boundaries of each of the“territories” can be defined using a 10 mile×10 mile grid system thatcan be used for further tagging or identifying content for example. Thatis, the system of the disclosure can segment each of the “remote” areasby mathematically deriving longitudes and latitudes for each territory,i.e., such that each territory possesses a 10 mile×10 mile area.

Once the second level areas are defined, the third level areas (sectors)can then be defined. The boundaries of each of the sectors can bedefined using a 1 mile×1 mile area grid system that can be used forfurther tagging or identifying content. That is, the system of thedisclosure can segment each of the territory areas by mathematicallyderiving longitudes and latitudes for each sector, i.e., such that eachsector possesses a 1 mile×1 mile area.

Once the third level areas are defined, the fourth level areas(quadrants) can then be defined. The boundaries of each of the quadrantscan be defined using a ¼ mile×¼ mile grid system that can be used forfurther tagging or identifying content. That is, the system of thedisclosure can segment each of the quadrant areas by mathematicallyderiving longitudes and latitudes for each quadrant, i.e., such thateach quadrant possesses a ¼ mile×¼ mile area, i.e. a 1,340 feet×1,340feet area.

Once the fourth level areas are defined, the fifth level areas (locals)can then be defined. The boundaries of each of the locals can be definedusing a 134 feet×134 feet grid system that can be used for furthertagging or identifying content, i.e. by breaking up each of thequadrants by using a 10×10 grid. That is, the system of the disclosurecan segment each of the local areas by mathematically derivinglongitudes and latitudes for each local, such that each local possessesa 134 feet×134 area.

Once the fifth level areas are defined, the sixth and lowest level areas(i.e. patches) can then be defined. The boundaries of each of thepatches can be defined using a 13.4 feet×13.4 feet grid system that canbe used for further tagging or identifying content, i.e. by breaking upeach of the locals by using a 10×10 grid. That is, the system of thedisclosure can segment each of the patch areas by mathematicallyderiving longitudes and latitudes for each patch, such that each patchpossesses a 13.4 feet×13.4 area.

For purposes of description, processing has been described herein asprocessing a “photo”. However, it should be appreciated that suchprocessing described as performed on a “photo” can be performed oncontent described as a photograph, digital photograph, digital photo,picture, video, digital video, image, digital image, and/or othercontent described using similar terminology. In general, the processingof the disclosure can be utilized with content or digital content,including a video, as may be desired.

In an embodiment of the disclosure, the process of determining a popularspot can begin with geographic segmentation that starts with theidentification of a known geographic area of interest that represents a“site”. For example, a “site” can be the area that encompasses theStatue of Liberty. In such example, smaller “spots” of uniquelyidentified areas can provide different vantage points within the site.Accordingly, a “bottom up” approach can be used in which spots areidentified and such identified “spots” can be accumulated into a site.Further, a first site can be geographically positioned next to oradjacent to a second site.

In accordance with at least one embodiment of the disclosure, theprocessing can include a determination of a “relevant universe” of allstored digital photos, i.e. “available photos” that can be used in theprocessing of the disclosure. Stored digital photos can be tied to anarea with a related longitude and latitude with such point containedwithin the area. A photo can include or be associated with metadata thatrepresents the location at which the photo was taken. Such locationmetadata can be in the form of a point defined in a coordinate system.For example, the point can be the longitude-latitude (i.e. “long-lat” orLL”) at which the photo was taken. Parameters can be established forvariables that can dictate whether a photo will or will not be includedin the processing of the system, i.e. whether a photo will be an “activephoto” or an “inactive photo”. The parameters can include the current(age of photo) and definition or protocol that can be used to determinethe current age of the photo, location type(s), various minimum volumes,popularity rankings, affinity groups, user identification andcredentials, and other attributes of a photo. Such attributes can beadjustable or variable through user interface with the system. Forexample, a photo can be deemed relevant and included, as an activephoto, if less than one year old as determined by the date that thephoto was taken. Such parameters that control whether a photo is anactive photo or an inactive photo, can be adjusted as desired. Forexample, with some spots, a photo might be relevant, and included as anactive photo, if less than 10 years old. With other spots, a photo mayonly be an active photo if less than 5 years old, for example.Additionally, photos can be included in the processing of the system, asan active photo, dependent on an interrelationship of the photo withother photos. For example, a density of photos can be taken intoconsideration where the system performs processing to determine how manyphotos there are in a particular area. If a threshold number of photosin an area has been achieved, then all of such photos in the area can beincluded as an active photo. On the other hand, if a threshold number ofphotos in an area has not been achieved, then such photos may be deemedto be inactive photos. That is, illustratively, photos in an area thathave not collectively achieved a predetermined density threshold can bemaintained as inactive photos in a database. The photos can bemaintained on a back end of the system for example. As more photos areadded to the particular area, the density of photos is the particulararea, such as a patch, will increase. Once the particular densitythreshold is attained in the area, the photos can be become active, i.e.by virtue that requisite density has been attained—and a patch is thusevolved into a spot, for example. Other variables or parameters canaffect whether a particular photo is included in processing as an“active photo” or whether such photo is “inactive”.

Inclusion of a photo or photos as active can be dictated, by theprocessing of the system, dependent on whether there are a sufficientnumber of photos of a particular patch or other location type orcombination thereof. Inclusion of a photo or photos as active can bedictated by attributes of a populated matrix of attributes orcharacteristics. For example, a “location type” of a photo can includetypes such as see, do, eat, drink, stay, shop or conceptual. Such typescan be associated with particular spots to see, particular activities toengage in, particular restaurants to eat at, particular restaurants todrink at, or particular hotels to stay at. Additionally, the inclusionor non-inclusion of a photo (as an active photo) can depend onattributes of surrounding areas. For example, photos in the top 20% of“local” areas, out of all local areas in a particular area, may beincluded in the processing as active photos. Such inclusion can becontrolled by the processing of the system.

A further processing component of the system of the disclosure caninclude establishment or generation of “virtual containers”. Thesevirtual containers can provide placeholders for segregation andaccumulation of photos. The virtual containers can correspond to and bedefined by each of the areas described above—including remote,territory, sector, quadrant, local, and patch areas. In at least someembodiments of the disclosure, each of the photos can be segregatedbased on location of the photo vis-à-vis the particular area or areas inwhich such location (of the photo) falls within. Processing can beperformed on an available photo to determine which area(s) or virtualcontainer(s) the particular photo belongs in. In such processing, aphoto can “cascade” down so as to be associated or tagged with thevarious virtual container(s) to which the photo belongs. Morespecifically, processing can be performed so as to associate or tag aphoto with: a remote area that geographically bounds the location of thephoto; a territory (within the tagged remote area) that bounds thelocation of the photo; a sector (within the tagged territory) thatbounds location of the photo; a quadrant (within the tagged sector) thatbounds location of the photo; a local (within the tagged quadrant) thatbounds location of the photo; and a patch (within the tagged local) thatbounds location of the photo.

A further processing component of the system of the disclosure caninclude an auto incremented and counting routine. For example, furtherphotos can be added into a particular patch. As the photos are added in,a count associated with the particular patch can be automaticallyincremented. The patches can be then be ranked and processing performedbased on such ranking A table of counts, for each patch, and rankings ofthe patches can be maintained by the system. A table of counts andrankings can be maintained based on the number of photos in patches.Additionally, a table of counts and rankings can be maintained based onattributes or characteristics of photos in the patches. For example, atable of counts and rankings can be maintained based on how many photosin each “patch” relate to places to eat. For example, a table of countsand rankings can be maintained based on how many photos in each patchrelate to events to see. The table of counts and rankings can bemaintained in a database for access by the system and updated oroverwritten in some periodic manner—or based on additional data that isinput into the system.

The processing as described herein, including components of theprocessing, can be executed periodically or at predetermined time(s).For example processing as described herein may be performed daily,hourly, weekly or other desired frequency and may be limited to or varyby particular identified geographic areas. Processing can be performedwhen a new photo is uploaded into the system, such as when a new photois input from a user. Processing can be performed upon request by arequesting, authenticated user over an established network. Processingcan be performed when a new photo or batch of photos is uploaded intothe system from a user, a database, or a third party server, forexample.

Hereinafter, further aspects of the systems and methods of the inventionwill be described.

In accordance with at least one embodiment of the disclosed subjectmatter, processing performed by the system can include accessing a photodatabase, which has been populated by photos from users and othersources. The photo database can contain location data regarding thephotos. The processing can include determining popularity of specificareas based on photos associated with each respective area. Theprocessing can include determining popularity of specific areas—such asthe number of photos in a “patch”. A patch that can be the smallest areademarcated by the processing of the system. An area, such as a patch,can include the relative strength of a preference provided by the user,positive or negative. Popularity of a particular area can be based onvarious attributes of one or more photos. Popularity can be based on thenumber of photos in a particular area or areas, such as in a patch.Popularity of an area can be based on attributes of a photo includinglocation data associated with the photo, time data associated with thephoto, and various other data associated or appended to the photo or toa cluster of photos.

The area of a “patch” has been described herein for purposes ofillustration. For example, a “patch” can evolve into a “spot” if densityof photos therein is sufficient. However, other areas can also beconsidered for and attain “spot” status, as described herein. Forexample, a geographic region such as a national state park might beprocessed to determine if such region possess sufficient density (ofphotos) such that the region should be deemed a spot.

Popularity of a particular area can also be based on “location type” andthe number of photos in such area that are associated with such locationtype. Accordingly, a given area (which can be a “patch”) can be saved inthe database (of the system) and tagged with a particular location type.In other words, the area can be associated with an attribute thatindicates the area is of the particular location type. Such associationor tagging can be performed utilizing a relational database, forexample. Then, a photo may be associated with the area based on thelocation (of the photo) being located within the boundaries of suchgiven area. Processing can then be performed to determine what “type” or“types” is the photo that was input. It may be the case that the photois of a “type” that is the same as the “location type”. Accordingly, theinput of such photo can contribute to a “location type count” or tallyof how many photos of the particular “type” are in the area of theparticular “location type”. In other words, if a photo in a particulararea is of a type that corresponds to a “location type” of the area—thenthat photo will contribute to what might be referred to as a “locationtype count” of that area. Such “count” processing can thus providepopularity of a particular area with regard to the particular type. Suchdata can then be used to compare different areas, such as to comparedifferent patches for comparative ranking. It should be appreciated thata given area is not limited to one “location type”. Additionally, agiven photo is not limited to be of one “type”. Accordingly, aparticular area can be, i.e. can possess an attribute of, one or morelocation types. A particular photo can be, i.e. possess an attribute of,one or more types. For example, a photo taken at a popular restaurant atNiagara Falls can be tagged as “where to see” and “where to eat”.Relatedly, the “spot” in which such restaurant is located can be taggedas “where to see” and “where to eat”. As a result, the particular photocan contribute to the “location type count” of the spot for both “whereto see” and “where to eat”.

In accordance with at least one embodiment of the disclosed subjectmatter, coding or instructions of the system can identify location types(of areas) and types (of photos) as may be desired. Location types thatare available for association or tagging of an area can be different fordifferent areas. For example, an area that has only one restaurant canbe tagged with a more general “location type” that can include “where toeat”. On the other hand, another area can be densely populated withrestaurants. Accordingly, the more general “location type” of “where toeat” can be further broken out into additional location types such as“Where to eat—American”, “Where to eat—Italian”, “Where to eat—Mexican”,and “Where to eat—fast food”.

For purposes of illustration, “location types” can include (1) “places”that can be organized by common characteristics such as consumer drivenactivities. Such “places” location type can be further differentiated toadditional location types or levels, or what might be referred to assub-levels. The further levels or sub-levels can include: a) where tosee; b) where to photograph; c) activities to do; d) where to eat; e)where to drink beverages; f) where to stay, and g) where to shop, forexample.

The location types can further include (2) “events” that can be tied tolocations that may be activity driven, group attended (like parades orfestivals) or newsworthy items that can occur more randomly.

The location types can further include (3) “things” that may includetangible items like candidates tied to a geographic area or intangibleconceptual items like a referendum.

The location types can further include (4) “virtual” that may includeuser defined or “other” items assessed for popularity, user or voterpreference.

As described above, the system can process geographic demarcations thatcan be referred to as “areas”. A particular type of area, i.e. thesmallest type of area, can be a “patch”. Each patch can have anattribute of one or more “location types”. A patch can be deemed morepopular as more photos are associated with either the patch in generalor with a location type(s) of the patch. A patch can be deemed topossess sufficient density of photos, i.e. may be deemed to be popularenough, to be a spot. The more popular spots can be referred to as “topranked spots”. Popularity of an area/spot can be determined byphotographic vote, where one or more users submit photos that yieldpopularity values. Popularity values for each of a number ofcharacteristics of the area can be determined from the photos andassociated clusters of photos. Data regarding each photo, clusters ofphotos, and various other data can be stored in a suitable database soas to perform processing as described herein. Accordingly, a user'sphoto can be the user's vote.

FIG. 1 is a diagram showing a photo ecosystem or ecosystem 10 inaccordance with at least one embodiment of the disclosed subject matter.The ecosystem 10 can include a photo system 100; a plurality of userdevices 20, 20′, 20″; and a third-party resource(s) 30. The variouscomponents of the ecosystem 10 can be connected and in communicationwith each other utilizing a suitable network 11. For example, thenetwork 11 can be in the form of or include the Internet, a privatenetwork, and/or some other network. The network 11 can be composed of aplurality of discrete networks that communicate with each other and withthe components illustrated in FIG. 1. It should be appreciated that thediagram of FIG. 1 is for purposes of illustration. The photo system 100can be in the form of one or more servers or in the form of adistributed computer system. While three user devices are illustrated inFIG. 1, the ecosystem 10 can include many more user devices—and may wellinclude thousands or millions of user devices. Each of such additionaluser devices can interact with photo system 100. Additionally, while onethird-party resource 30 is illustrated, it should be appreciated thatmany third-party resources can be utilized and included in the ecosystem10. Additional systems, servers, processors, and other processing assetsand/or database assets can be included in the ecosystem 10.

The photo system 100 can perform various processing as described hereinbased on instructions stored in the database portion 120. The photosystem 100 can store instructions so as to provide the processingdescribed herein and can store the various photos, i.e. photo data thatcan include digital image data (of the image itself—a reproduction ofwhat would be viewed by the human eye) as well as metadata about thephoto, that is processed by the photo system 100. The photo system 100can be connected to the network 11 so as to receive data from a varietyof devices. The devices can be stationary in nature, like a desktopcomputer used for planning future location visits across the earth. Thedevices can be mobilized to include data identifying a current locationand for establishing an area that is proximate to the user—and that isof immediate interest to the user. The photo system 100 can interfacewith the user device 20 so as to provide a variety of features to theuser device 20. The photo system 100 can input data from the user device20. The photo system 100 can output data to the user device 20.

The photo system 100 can include a computer processor (CP) 110 and adatabase portion 120. The CP 110 can include a variety of processingportions as illustrated. Additionally, the database portion 120 caninclude a variety of database portions as illustrated.

The CP 110 can include a general processing portion 111. The generalprocessing portion 111 can perform various general processing so as toperform general operations of the photo system 100. The generalprocessing portion 111 can perform processing based on instructionscontained in the database portion 120. The general processing portion111 can perform any of the processing required or desired (so as toprovide functionality of the photo system 100) that is not handled bythe more specialized processing portions 112-116. However, it should beappreciated that the processing performed by the general processingportion 111 can be specialized in and of itself so as to provide thevarious functionality described in this disclosure.

The CP 110 includes the area segmentation processing portion 112. Thearea segmentation processing portion 112 can handle segmentationprocessing as described herein. Accordingly, the area segmentationprocessing portion 112 can handle segmentation of an area, for examplethe world, into first level areas, second level areas, third level areasand so forth. The area segmentation processing portion 112 can handlesegmentation down to the level of a “patch”. The area segmentationprocessing portion 112 can handle various related processing.

The CP 110 also includes the photo input processing portion 113. Theprocessing portion 113 can handle photo input processing as describedherein. Such processing can include various processing related to theinput of a photo, interfacing with a user in conjunction with input of aphoto, processing that is performed once the photo is input, processingof metadata associated with the photo, and various related processing.The CP 110 also includes the spot generation processing portion 114. Theprocessing portion 114 can handle spot generation processing asdescribed herein. Such processing can include generation of a “spot”once predetermined thresholds have been attained such that a particulararea is to be identified as a spot, generation and saving of data inconjunction with generation of a spot, and various related processing.

The CP 110 can also include the user engagement processing portion 115.The processing portion 115 can handle user engagement processing asdescribed herein. Such processing can include a wide variety ofprocessing related to user engagement including using credentials toidentify a current user, setting up a new user on the system,establishing preferences or settings of a user, and various relatedprocessing. The CP 110 can also include the collective user processingportion 116. The processing portion 116 can handle collective userprocessing as described herein. Such processing can include variousprocessing related to crowd sourced information, user review processing,user rating processing, user feedback processing, other processing thatrelates to interfacing with a plurality of users or other persons on anaggregated basis, and various related processing.

The photo system 100 can include the database portion 120. The databaseportion 120 can include a general database 121. The general database 121can include various data used by and/or generated by the generalprocessing portion 111.

The database portion 120 can include an area segmentation database 122.The area segmentation database 122 can include various data used byand/or generated by the area segmentation processing portion 112.

The database portion 120 can include a photo database 123. The photodatabase 123 can include various data used by and/or generated by thephoto input processing portion 113.

The database portion 120 can include a spot generation database 124. Thespot generation database 124 can include various data used by and/orgenerated by the spot generation processing portion 114.

The database portion 120 can include a user engagement database 125. Theuser engagement database 125 can include various data used by and/orgenerated by the user engagement processing portion 115. The databaseportion 120 can include a collective user database 126. The collectiveuser database 126 can include various data used by and/or generated bythe collective user processing portion 116.

The photo system 100 can be in the form of or include one or morecomputer processors and one or more database portions 120. The photosystem 100 can include or be in the form of a server. Various furtherdetails of the photo system 100 and the processing performed thereby aredescribed below.

FIG. 2 is a high level flowchart illustrating processing that can beperformed by the photo system 100, in accordance with principles of thedisclosed subject matter. The processing can start in step 400 withinitiating of photo processing. For example, step 400 can includeenabling the system 100 or turning the photo system 100 “on”.

The processing of FIG. 2 can pass from step 400 onto step 401. Step 401illustrates various processing that can be performed by the system 100.The processing illustrated in step 401 can be performed in serial or inparallel relative to each other and need not be performed in theparticular order illustrated in FIG. 2. In a particular implementationof the system 100, some processes of FIG. 2 can be performed or enabledand other processes may not be performed or enabled.

With reference to step 401 of FIG. 2, in step 500, the system canperform area segmentation processing. Further details are describedbelow with reference to FIG. 3. In step 520, the system 100 can performphoto input processing. Such processing can include the input of photosin real time or in batch manner, for example. Further details aredescribed below with reference to FIG. 6. In step 560, the system 100can perform spot generation processing. Further details are describedbelow with reference to FIG. 9. In step 700, the system 100 can performuser engagement processing. Further details are described below withreference to FIG. 14. In step 810, the system 100 can perform specialtyprocessing. In step 950, the system 100 can perform collective userprocessing wherein the system engages with a plurality or mass of usersto perform affinity groups processing, user following processing,assessment of ratings view processing, and related processing. In step820, the system 100 can perform general processing. The variousprocessing performed in step 401 can be performed by one or more of theprocessing portions in the CP 110. Further details are described below.

FIG. 3 is a flowchart showing further details of the system 100 performsarea segmentation processing, which can be called from the processing ofFIG. 2, in accordance with principles of the disclosed subject matter.As illustrated, the processing starts in step 500 with segmentation of apredetermined geographic area, i.e., the world in this illustrativecase. As reflected at 500′, in initial segmentation of the world, theworld can be a current parent area and “remote areas” can be childareas. That is, the processing of FIG. 3 illustrates processing in whicha top down approach is utilized. In such processing, an initial area tobe segmented can be segmented at a first level, each of the first levelsegmentations can then be segmented at a second level, and so forth—soas to attain a desired segmentation. Alternatively, a bottom up approachcan be utilized. In a bottom up approach, the lowest level area can besegmented, a predetermined number of the lowest level areas can then beaggregated together so as to form a next higher up level, areas in thenext higher up level area can then be aggregated so as to perform afurther next higher up level, and so forth. In such manner, a desiredsegmentation can be attained. Accordingly, with bottom up segmentationprocessing, the system builds up from smallest child to largest parent.With top-down segmentation processing, the system builds down fromlargest parent to smallest child. In accordance with at least oneembodiment of the disclosure, the largest parent can be the world,whereas the smallest child can be demarcated as a “patch” as describedherein.

After the processing is initiated in step 500, the process passes ontostep 501. In step 501, for the current parent area, the system canidentify an anchor point for the first child area (or for the currentchild) and assign such anchor point as a current anchor point. Theanchor point can be long-lat coordinates or other coordinates.

After step 501, the process passes onto step 502. In step 502,processing is performed to assign an area identifier and identifyboundaries of the area. In such processing, subroutine 510 of FIG. 4 canbe called. As reflected at 502′, the area identifier can be a uniqueidentifier that can be a longitude—latitude point (long-lat) of a cornerof the area. Accordingly, in one embodiment of the disclosure, oneanchor point can identify location of the area and a height, width, orother geometrical extent can be used to identify boundaries of theparticular area. In some embodiments of the disclosure, an upper left(in long-lat coordinates) and lower right (in long-lat coordinates) ofthe area can be used so as to define the area. With either approach, aunique identifier can also be assigned to each area so as to be used inprocessing of the area. After step 502, processing passes onto step 503.

In step 503, the process determines if the current area, which can bereferred to as a parent area, can be segmented into a further child(i.e. in addition to the children that have already been formed out ofthe parent area). Such processing component is indicative of a top downapproach, in contrast to a bottom up approach. In other words, thedecision processing of step 503 determines if the current area has beenfully segmented out such that no further segmentation is needed (inorder to segment the current area). As reflected at 503′, suchdetermination processing of step 503 can be based on whether a boundaryof the current area coincides with an anchor point of a previouslyprocessed area. If a boundary of the current area does coincide with ananchor point, such can indicate that the processing has reached the endor limit of the current area. In some embodiments, the processing canadvance in a horizontal manner—to segment across an area—until aboundary is reached. Then, the processing can start a new “row” belowthe row that was just segmented. In such manner, for a given area, theprocessing can advance across and drop down a row; across and drop downa row; across and drop down a row; and so forth until the particulararea has been fully segmented. However, other methodologies can be used.

With further reference to step 503 of FIG. 3, if the decision of step503 is yes, then the processing passes onto step 504. In step 504, basedon an outer most boundary of the current child area, the process canassign a point on such boundary as a new “current anchor point”. Morespecifically, the process may assign the upper point on a right boundaryline as the new “current anchor point”. If the upper point on the rightboundary line has already been assigned to be an anchor point, or ispositioned outside the current area being processed—then the system canknow that the particular row is completed. Upon such determination, theprocess can “drop down” a row so as to segment the next row.

Once the new current anchor point is identified/determined in step 504,the processing passes back to step 502. In step 502, processingcontinues as described above.

On the other hand, it may be determined in step 503, that the currentparent area cannot be segmented so as to form a further child. In otherwords, a no determination in step 503 indicates that the current parentarea has been fully segmented into child areas. As a result, the processpasses from step 503 onto step 505.

In step 505, the processing determines if there are more parent areas(at the current level) to segment. If yes, then the process passes ontostep 506.

In step 506, the next parent area to segment is assigned to be thecurrent parent area. The process passes from step 506 back to step 501.Processing then continues as described above. On the other hand, it maybe determined that there are not more parent areas (at the currentlevel) to segment. Such no determination in step 505 indicates that allthe areas at the current level have been segmented out, i.e. such thatchildren of the current parent have been created. Accordingly, theprocess passes from step 505 onto step 507.

In step 507, the processing determines if segmentation should beperformed down a further level. If yes in step 507, the processingpasses onto step 508. In step 508, the process advances to the nextlower level. Accordingly, the first child area (of the children areasjust created) becomes the current parent area. Also, the level of thenew parents is assigned to be the current level. More generally, asreflected at 508′, the newly created children now become the parents.The processing passes back to step 501. In step 501, the processingcontinues as described above.

It may be determined in step 507, that segmentation is not to beperformed down a further level, i.e. that the segmentation processinghas indeed attained the lowest level to be segmented. Such lowest levelcan be the “patch” level as described herein. As reflected at 507′, a nodetermination in step 507 reflects that all of the segmentation areasnow have unique identifiers and that all boundaries of the areas havebeen formed. Accordingly, the process passes from step 507 onto step509. In step 509, the system has completed the segmentation processing.Accordingly, the process returns to FIG. 2.

FIG. 4 is a flowchart showing details of “processing is performed toassign area identifier and identify boundaries of the area” ofsubroutine 510 as called from FIG. 3, in accordance with at least oneembodiment of the disclosed subject matter. As shown, the process startsin step 510 and passes onto step 511. In step 511, the system assigns aunique area identifier to the current anchor point. In one embodiment,the unique area identifier can correspond to one corner of the areausing longitude and latitude values. Then, the process passes onto step512.

In step 512, the system can retrieve current X, Y advance parameters forthe current level. The current advance parameters can dictate magnitudeof a new area to be formed, or in other words to be segmented out. Ifthe X, Y advance parameters are 10 miles, 10 miles, respectively—then anarea that is 10 miles wide and 10 miles high will be created. Such X, Yadvance parameters can be utilized to create the segmentation areasdescribed above. Such segmentation areas can include remote, territory,sector, quadrants, local, and patch. Accordingly, it should beappreciated that as the system performs segmentation processing, thesystem can retrieve the particular X, Y advance parameters thatcorrespond to the current level being processed. The X, Y advanceparameters can be selected so as to evenly segment a current parent areainto children areas. In at least some embodiments, it may be the casethat all the children areas are not of the same magnitude in squaremiles or in square feet, for example. Additionally, the advanceparameters can be more complex than X, Y advance parameters. Morecomplex advance parameters can be used when segmenting more complexgeographical areas, such as the circular curvature of the world orglobe.

After step 512, the process passes onto step 513. In step 513, based onthe advance parameters, the system identifies corner points and/orboundaries of the current child area. As a result, as reflected at 513′,the CP 110 has now created a new current area.

After step 513, the process passes onto step 514. In step 514, theprocess returns to FIG. 3. Specifically, the process passes onto step503 of FIG. 3.

FIG. 5 is a diagram showing segmentation of a remote segmentation area150. In the example, a “remote” area is the current parent area and“territory” children areas are being formed/segmented out of such parentarea 150. As shown in FIG. 5, segmentation of the area 150 (currentparent area) into children areas is almost complete, i.e. with fivechildren areas to be formed or further segmented out. The current childarea 160 has been assigned an area ID (i.e. an area identification orarea identifier) of T096. Such area T096 possesses an anchor point 161.In this example, the anchor point 161 can be an upper left hand corner(in long-lat coordinates) of the area T096. The area T096 can alsoinclude a boundary point 162. The boundary point 162 can be provided atthe upper right-hand corner of the area T096. The boundary point 162 mayhave been identified by the current X, Y advance parameters as describedabove with reference to step 512 of FIG. 4. Once the territory area 160is saved into memory, the processing can then use the boundary point 162as the next anchor point—for the next territory area to be segmentedout. Such is illustrative of the processing of step 504 of FIG. 3. Thearea 160 can be defined based on a predetermined height (as shown inFIG. 5) so as to define the two-dimensional area. The area can bedefined so as to be square—and thus the distance between the points 161and 162 can also serve to define the height (as shown in FIG. 5) of thetwo-dimensional area 160, as well as the height.

As illustrated in FIG. 5, after the formation of the area 160, thesystem has five more territory levels to form (in the remote area 150)in order to fully segment out the remote area 150. The system, i.e. theCP 110, can determine that segmentation is complete once (1) an upperright boundary point 162 of an area corresponds to a right hand boundaryof the area 150 and (2) a lower right boundary 162 corresponds to alower boundary of the area 150, for example.

Once segmentation of the current parent area 150 is completed, then theprocessing can advance to the next parent area (at the current level).That is, the processing can advance from the remote area 150 onto theremote area 151.

FIG. 6 is a flowchart showing details of the “photo system (PS) 100performs photo input processing” of step 520 of FIG. 2, in accordancewith principles of the disclosed subject matter. Such processing caninclude the inputting of a photo or photos with either batch or realtime processing, for example. As shown, the process starts in step 520and passes onto step 521.

As reflected at 520′, a “photo” or “photo data” can include both imagedata (that represents a reproduction of the image that was viewable bythe human eye) and various metadata (that contains data about the photo,such as date/time that the photo was taken and location of the photo).The location data of a photo can be in the form or include a point orgeographical point. For example, the point can be the longitude-latitude(long-lat) at which the photo was taken.

In step 521 of FIG. 6, the system determines that one or more photos arein queue for processing of the one or more photos by the system 100.Accordingly, the processing of step 521 assumes that one or more photosare in queue for processing. After step 521, the process passes ontostep 522.

In step 522, the system determines if the one or more photos areaggregated (in queue) in a batch manner. In other words, processing candetermine if a group of photos has been uploaded to the system in abatch manner. In such situation, it may be desirable or beneficial tocapture the fact that such photos were input together in a batch manner.In other words, it may be beneficial to capture such interrelationshipbetween such uploaded photos. The processing of step 524 provides suchcapture of interrelationship between the photos. That is, if yes in step522, the process then passes onto step 524. In step 524, for each photo,the system assigns both a photo ID (identification or identifier) and abatch ID. The batch ID can be common to all photos in the particularbatch. Accordingly, the interrelationship or association between thephotos in the batch can be captured in the database portion 120. Asshown at 524′, the batch ID can be used to perform “commonalityprocessing” for the photos in the batch. After step 524, the processingpasses onto step 525.

On the other hand, it may be the case in step 522 that the photos arenot aggregated in a batch manner or that there is only one photo inqueue for processing. As a result, the process passes from step 522 ontostep 523. In step 523, for each photo, the system assigns a photo ID.The process then passes onto step 525.

In step 525, the first photo to be processed is assigned to be thecurrent photo. Then, in step 530, the system processes the current photoso as to integrate such photo into the system. Such processing caninclude integration into the database and photo inventory of the system.Subroutine 540, of FIG. 7, can be called upon so as to process eachphoto. Then, after step 530, the processing passes onto step 531. Instep 531, a determination is performed by the system of whether there isanother photo to be processed. If yes, then the processing passes ontostep 532.

In step 532, the system retrieves the next photo and assigns suchretrieved photo to be the “current photo” in the processing. Processingthen passes back to step 530. Processing then continues as describedabove.

Alternatively, it may be determined in step 531, that there is notanother photo to be processed. Accordingly, a no determination isdetermined in step 531. As shown at 533, such reflects that all photo orphotos that were input by the system have been processed. With suchdetermination, the processing passes from step 531 onto step 534. Instep 534, photo input processing is terminated for the particularphoto(s) or for the particular batch of photos.

FIG. 7 is a flowchart showing further details of the system “processescurrent photo so as to integrate such photo into the system” ofsubroutine 540 as called from FIG. 6, in accordance with at least oneembodiment of the disclosed subject matter. As shown, the process startsin step 540 and passes onto step 541. In step 541, the systemdetermines, based on metadata of the photo, does the photo possessmetadata that satisfies predetermined criteria. For example, theprocessing of step 541 can relate to determining whether the metadatacontains appropriate location data that can include longitude andlatitude data, appropriate date and time data, data indicating a sourceof the image such as a particular user, and other requisite data. If noin step 541, the process passes onto step 544. In step 544, the photocan be placed into an archive database or other suitable database andwill not be placed in a virtual container, in at least one embodiment ofthe disclosure. In other words, the photo will not be placed into theactive inventory of the system. A communication can be sent to theoriginating user indicating that the metadata associated with the photowas insufficient to be included in the photo system.

If a yes determination is determined in step 541, then the processpasses onto step 542. In step 542, based on metadata of the photo, thesystem determines whether the photo possesses data to satisfypredetermined verification requirements. For example, was appropriatebiometric data included with the photo for verification of the photo,were other security protocols satisfied, and/or was an appropriate IPaddress of a source user device received. If no, than the processingpasses to step 544. In step 544, processing is performed as describedabove.

If yes in step 542, the process passes onto step 543. In step 543, theprocessing can determine, based on the metadata of the photo, does thephoto satisfy any other applied constraints. If no, then the processingagain passes to step 544.

On the other hand, if yes in step 543, then the process passes onto step545. In step 545, the photo is tagged as satisfying all requiredcriteria for placement into a virtual container or in other words forthe photo to be placed in the active inventory of the system as anactive photo. As a result, a communication can be sent to the user. Suchcommunication can be of a congratulatory nature indicating that his orher input photo has been successfully input into the photo system 100.Then, the processing passes onto step 546.

In step 546, processing is performed to place the photo into a virtualcontainer. Subroutine 550 can be invoked to process the photo, as shownin FIG. 8. As shown in FIG. 7 and reflected at 546′, a particular area,such as the world or planet, can be first segregated into one of theapproximately 19,700 remote areas. The input photos can cascade down andaccumulate in accordance with established parameters to the lower levelsof territories, sectors, quadrants, locals, and ultimately patches.

FIG. 8 is a flowchart showing in further detail subroutine 550 (calledfrom the processing of FIG. 7) that can include processing to place thephoto into a virtual container, in accordance with at least oneembodiment of the disclosure. As is shown at 550′, the processing ofFIG. 8 can include various components. The processing can accumulatephotos through a cascading process to segregate photos geographicallyinto virtual containers that cascade through 6 levels of refinementbased upon volume relevance. The processing can count the photos withineach of the virtual containers and test for volume relevance. In otherwords, the processing can determine volume relevance based on a count ofphotos in a virtual container.

The processing of FIG. 8 starts in step 550 and passes onto step 551. Instep 551, location data of the photo is retrieved from the appropriatedatabase. Then, in step 552, the process identifies the particularlevel-1 area to which the location data is associated and associates thephoto to the identified level-1 area. The level-1 area can be one of the“remote” areas as described herein. As reflected at 552′, the area towhich the particular photo is associated can be the area in which thelongitude and latitude coordinates of the photo are bounded. In otherwords, the area to which the particular photo is associated can be thearea in which the photo is located. Then, the process passes onto step553.

In step 553, in the identified level-1 area, which was identified instep 552, the processing determines the level-2 area to which the photois associated. The processing then associates the photo to theidentified level-2 area. Such identified area is then allocated a count.

In step 554, in the identified level-2 area, which was identified instep 553, the processing determines the level-3 area to which the datais associated. The processing then associates the photo to theidentified level-3 area. Such identified area is then allocated a count.

In step 555, in the identified level-3 area, which was identified instep 554, the processing determines the level-4 area to which the photois associated. The processing then associates the photo to theidentified level-4 area. Such identified area is then allocated a count.

In step 556, in the identified level-4 area, which was identified instep 555, the processing determines the level-5 area to which the photois associated. The processing then associates the photo to theidentified level-5 area. Such identified area is then allocated a count.

In step 557, in the identified level-5 area, which was identified instep 556, the processing determines the level-6 area to which the photois associated. The processing then associates the photo to theidentified level-6 area. Such identified area is then allocated a count.The level 6 area can be a patch or patch area.

Accordingly, as shown in FIG. 8, cascade processing can be utilized soas to associate an input photo into a respective virtual container foreach of the levels. After step 557 of FIG. 8, the processing passes ontostep 558. In step 558, photo placement processing is completed for theparticular photo. As reflected at 558′, the processed photo, as well asphotos that have been previously processed are now accumulated withinthe various virtual containers. Such photos can be in the many tothousands or millions.

Each “area”, as described herein, can constitute or include a “virtualcontainer” and/or be represented by a virtual container. Accordingly,for example, each of the “patches” as described herein can constitute avirtual container.

In step 558, the processing can pass back to step 531 of FIG. 6.Processing can then continue as described above.

FIG. 9 is a flowchart showing further details of the “system performsspot generation processing” subroutine 560 of FIG. 2, in accordance withprinciples of the disclosed subject matter.

As described above, a “patch” can be a smallest area of the variousareas that are segmented out. A “patch” can be approximately 13×13 feet,for example. In “spot” generation processing, a “patch” can be elevatedto a “spot”—depending on attributes of the particular patch. Suchattributes can include the density of photos in the particular patch. Ifthe density of photos surpasses a predetermined threshold, the “patch”can be elevated to the stature of a “spot”. Once elevated, such spot canbe subject to various processing, such as being identified in searchresults and/or be given a higher ranking or rating.

As shown in the processing of FIG. 9, the process starts in step 560 andpasses onto step 561. In step 561, the system watches for an event to beobserved that invokes spot generation (SG) processing. In performingsuch processing of step 561, subroutine 570 can be called upon orinvoked. Further details are described with reference to FIG. 10 below.

Relatedly, as is shown at 561′, the process of step 561 can be performedat various times. For example, the processing of step 561 can beperformed daily, hourly, weekly, or at other desired frequency and maybe limited to or vary by particular identified geographic area. Theprocessing of step 561 can be performed when a new photo is uploadedinto the system. The processing of step 561 can be performed uponrequest by a requesting user over an established network. Furtherdetails are described below with reference to FIG. 10.

Based upon the system watching for an event in step 561, in step 563′,the system can perform a determination of whether an event was indeedobserved. If no in step 563′, the system continues to watch for an eventas reflected at 562. Accordingly, the processing loops back to step 561and continues as described above.

On the other hand, if yes in step 563′, the process passes onto step563. In step 563, if the event, which was identified in step 561,included an input photo—then a subroutine can be invoked to process thephoto. Specifically, the subroutine 540 of FIG. 7 can be invoked toprocess the photo. Then, the process passes onto step 564. In step 564,based on attributes associated with the event, the geographic regionupon which to perform spot generation is determined. Then, the processpasses onto step 565.

In step 565, for the identified geographic region, spots in such regionare generated based on photo content in such geographic region. In otherwords, patch areas in the identified geographic region can be evolved tobe spots. Subroutine 600 can be called as shown in further detail inFIG. 11 and described below.

After step 565, the process passes onto step 566. In step 566, thesystem generates a communication that patches in the particular regionhave been involved to spots. For example, a communication can begenerated and output to a requesting user or to a user that submitted aphoto that contributed, in some particular way, to the promotion of apatch to spot. Then, the process passes onto step 567. Step 567 reflectsthat the processing has been completed. In other words, the processingof the subroutine 560, as shown in FIG. 9, is completed. It should beappreciated that various other processing and subroutines as shown inFIG. 2 can be continued or further called upon as otherwise describedherein.

As reflected at 561″, the described processing relates to “patches”.However, similar processing can be applied to any virtual containers ofa level, such as “local” (level-5) or “quadrants” (level-6), forexample. A “local” area that has evolved into a spot can be described asa “local-spot”.

FIG. 10 is a flowchart showing in further detail the “system watches foran event to be observed that invokes spot generation processing”subroutine 570, as called from FIG. 9. The processing of step 570 ofFIG. 10 can include various components 571, 572, 573, 574, and 575.These various processing components can be performed in parallel usingrespective subroutines that can be performed by the system 100. In step571, the system can determine if a time marker has been attained basedon some predetermined periodicity. In step 572, the system can determineif a new photo has been loaded into the system. In step 573, the systemcan determine if a threshold number of photos have been loaded into thesystem. In step 574, the system can determine if a threshold number ofphotos of a particular type or attribute have been loaded into thesystem. In step 575, the system can determine if a user or administratorhas requested spot generation (SG) processing.

Accordingly, the system can determine if various “triggers” of steps571, 572, 573, 574, and 575 have been satisfied—so as to enable oractivate the processing of each of such steps. Enablement (i.e. whetherthe processing of such steps is available) of any of such steps 571,572, 573, 574, and 575 can be performed through suitable settings, whichcan be controlled by an administrator or user. Additionally, thresholds,parameters, or other attributes of any of the steps 571, 572, 573, 574,and 575 can be adjusted by an administrator or user as may be desired.It should be appreciated that processing of some of the steps 571, 572,573, 574, and 575 may be enabled, whereas other steps are not enabled.

With further reference to FIG. 10, if a yes determination is determinedin any of the various steps 571, 572, 573, 574, and 575, the processingcan pass onto step 576 of FIG. 10. In step 576, based on the particularrequest, the system can attach control data to the processing request.This control data can control processing of the request. For example,the request can be limited to a particular geographic area, such thatonly “patches” in such geographic area are processed for possibleelevation to spot status.

After step 576, the process passes onto step 577. In step 577, theprocessing passes back to FIG. 9—and specifically passes to step 563′.

FIG. 11 is a flowchart showing further details of a “spot generationprocessing” subroutine 600, as called from FIG. 9, in accordance withprinciples of the disclosed subject matter.

More specifically, the processing of FIG. 11 relates to theconsideration of patches, in a predetermined geographical region, thatmay be promoted to the status of spots. The patches in the particulargeographic region, or in other words an “identified geographic region(IGR)”, can be considered for promotion based on photo content in suchgeographic region.

The processing of FIG. 11 starts in step 600 and passes to step 601. Instep 601, the system determines the various “patches” that are in theidentified geographic region (IGR) AND that have at least one (1) count,i.e. at least one photo associated with the patch, in accordance with atleast one embodiment of the disclosed subject matter. As describedabove, a patch can be in the form of or include a virtual container inwhich photos are placed (or associated with). An identified geographicregion may be all the patches in a particular “local”; all the patchesaround a particular point of interest; all the patches in a particulargeographic region, such as along a coast line; or all patches that havesome other common attribute or that are identified for processing andsome suitable manner Additionally or alternatively, patches can beprocessed in some sequential manner. Accordingly, the processing of step601 contemplates that not all patches in the world or country, forexample, will be processed at the same time. Rather patches can becarved out and processed in groups and/or processed sequentiallydependent on processing capabilities and bandwidth that is available.

After the processing identifies the patches to processed in step 601,the processing passes onto step 602. In step 602, the system identifiesthe first patch that is in the IGR and tags such as the current patch.Such tagging can identify the particular patch as being the next patchto be processed. After step 602, the process passes onto step 603.

In step 603, the system retrieves data, including photo count, that isassociated with the current patch. In other words, how many photos havebeen associated with the particular patch. Then, the process passes ontostep 604.

In step 604, the system determines, for the current patch, if the numberof photos contained therein exceed a threshold. For example, thethreshold could be 20 photos that have been associated with the currentpatch. If 20 photos have not been associated with the current patch,then a no is rendered in the processing of step 604. As a result, theprocess passes from step 604 onto step 607.

On the other hand, a yes determination may be rendered in the processingof step 604. Such yes determination reflects that the current patch hasindeed attained 20 photos associated therewith. Based on the yesdetermination in step 604, the process passes onto step 605. In step605, the current patch is tagged (by the system) to constitute a “spot”.In accordance with at least one embodiment of the disclosure, a patchdesignated as a spot will then be rendered in search results, as furtherdescribed below. On the other hand, a patch that has not been involvedto be a spot may not be rendered in search results. After step 605 ofFIG. 11, the process passes onto step 606. In step 606, the systemperforms “type tagging” for the current patch, which has now attainedspot status. Such elevated patches can be deemed a “patch-spot”. Toperform the processing of step 606, subroutine 610 can be called asdescribed below with reference to FIG. 12. The type tagging of step 606can also be performed for patches that have not attained thepredetermined threshold (step 604).

After step 606, the process passes onto step 607.

In step 607, the system identifies the next patch, if any, that is inthe identified geographic region (IGR) and tags such next patch as thecurrent patch. As reflected in the processing of step 607′, the systemmay determine that there is not a next patch. As a result, the processpasses onto step 609. In step 609, the processing passes back to FIG.9—and specifically passes onto step 566 of FIG. 9.

With further reference to FIG. 11, and in the situation that there isindeed a further patch or next patch identified in step 607, theprocessing passes from step 607 back to step 603. In step 603, thesystem retrieves data, including photo count, that is associated withthe current patch. Processing then continues as described above.

As shown at 600′ (FIG. 11), a “spot” status can reflect an elevatedstate or status of any of the 6 types of areas, and not just a “patch”.Relatedly, the processing of FIG. 11, and in particular step 604, isbased on whether a particular photo count has been attained by aparticular patch. However, the systems and methods are not limited tosuch particulars. For example, a “spot” can be a local or other areathat has been elevated to be a “spot” due to (a) number of photos in theparticular area, (b) same types of photos in the particular area thatexceed some threshold, and/or (c) based on other popularity rankings,attributes, etc. that have been attained in the particular area.

In accordance with principles of the disclosed subject matter, thelocation of a photo can be a point, i.e. a longitude/latitude point(long/lat point). The area to which the photo is to be associated can bedetermined mathematically—by determining the particular area in whichthe photo is bounded. Relatedly, there may by a case in which an area,such as a patch, is not fully encompassed with an identified geographicregion (IGR). For example, an area might be generated to be around alandmark or an area might be drawn or designated by a user. Such areamight be split or cross-over two or more IGRs. In such a situation,settings may be provided to control what constitutes “in” an identifiedgeographic region, e.g. (a) fully encompassed within, or (b) partiallywithin. Thus, for example, if a particular patch is only partially in anIGR to be processed (step 601 of FIG. 11), then such patch may indeed beprocessed based on an inclusive setting. However, it may be that anothersetting dictates that a particular patch has to be fully within an IGR.Other parameters and/or attributes of a patch (or other area) and/or aparticular IGR can be utilized so as to dictate whether a patch will beprocessed or will not be processed in a particular IGR.

FIG. 12 is a flowchart showing in further detail the system performs“type tagging” for the current patch of subroutine 610 of FIG. 11, inaccordance with principles of the disclosed subject matter.

The process begins in step 610 and passes onto step 611. In step 611,the system performs “type tagging” for the current patch for a type-Aphoto. The processing of step 611 can call upon the subroutine 620 ofFIG. 13. Then, the process passes onto step 612.

In step 612, the system performs “type tagging” for the current spot fora type-B photo. In step 614, the system performs “type tagging” for thecurrent spot for a type-Z photo. As reflected at 613 of FIG. 12, itshould be appreciated that processing can be performed for any desirednumber of “types” of photos. For example, as shown at 613′, additionalphoto types can include a variety of location types.

For purposes of illustration, subroutine 620 of FIG. 13 shows typetagging to determine whether a particular spot has one or more type-Aphotos. However, the processing as illustrated in FIG. 13 can be appliedto any of the types illustrated in FIG. 12 or other types, as may bedesired.

Accordingly, in the various processing of FIG. 12, the system determineswhat type of photos are associated with the particular spot. Asdescribed above, a particular one photo can be tagged as two or moretypes. Thus, for example, a particular photo might be tagged in bothstep 611 and step 612 of FIG. 12.

After all the types have been processed in FIG. 12, the process passesonto step 615. In step 615, the processing returns to FIG. 11—andspecifically passes onto step 607 of FIG. 11.

FIG. 13 is a flowchart showing further details of the system performs“type tagging” for the current spot for a type-A photo of subroutine620, in accordance with at least one embodiment of the disclosed subjectmatter. As shown, the process starts in step 620 and passes onto step621.

In step 621, the system determines, for the current spot, if any photoscontained therein are tagged as a type-A photo. For example, a type-Aphoto might be a “parade event”, for example, as reflected at 621′.However, it is appreciated that a photo can be possess or be attributedwith any of a variety of types. Such “type” can include any “thing” orattribute that is associated with the particular photo. For example, the“thing” that is associated with the photo might be a particular timewindow in which the photo was taken.

If yes in step 621, the process passes onto step 622. In step 622, thesystem determines the number of photos that are tagged as type-A. Then,in step 623, the system associates data (from step 622) with theparticular spot so as to be searchable by a user. Then, the processingpasses onto step 625. In step 625, the processing returns to FIG. 12 andstep 612. In step 612, the processing continues as described above—toprocess the current spot to identify further types of photos in suchspot.

On the other hand, a no determination may be rendered in step 621.Accordingly, the processing passes from step 621 onto step 624. In step624, the system has determined that the current spot does not possessany type-A photos. The system can then store such determination. Then,processing passes onto step 625. Processing then continues as describedabove.

As reflected at 623′ of FIG. 13, a searching user may enter searchcriteria of type-A in a certain number. For example, a user may searchfor a particular area, i.e. a particular geographical area, that has atleast 10 type-A photos. Additionally, search criteria may not beconstrained or dictated by a certain number of a particular type ofphoto in a spot. Rather, search criteria can utilize top ranked spots orother areas. In such processing, the top ranked spot or spots can bereturned as search results regardless of the particular number of aparticular type of photo associated with such spot.

FIG. 14 is a flowchart showing in further detail the subroutine 700,system performs user engagement processing, invoked or called upon fromFIG. 2. The processing of subroutine 700 can include both step 701 andstep 702, in accordance with embodiments of the disclosed subjectmatter. In particular, the processing of FIG. 14 relates to interfacingwith a user device, which is associated with a human user, to input botha new photo that can include image data and attributes or metadataregarding such new photo. The processing of steps 701 and 702 can beperformed in parallel or in serial and need not be performed in theparticular manner illustrated in FIG. 14.

In step 701 of FIG. 14, the system interfaces with a user device toinput a new photo. In such processing, subroutine 710 can be called uponor invoked. Such subroutine 710 is illustrated in further detail belowwith reference to FIG. 15. As reflected at 701 of FIG. 14, the system100 can also interface with other systems to input photos in batch orserial manner, for example.

In step 702 of FIG. 14, the system interfaces with a user device toinput attributes of the photo. In such processing, subroutine 730 can becalled upon or invoked. Such subroutine 730 is illustrated in furtherdetail below with reference to FIG. 16.

In step 760 of FIG. 14, the PS interfaces with the user device, i.e. theuser, to perform photo user processing. In performing such processing, asubroutine 760 can be called or invoked. Such subroutine 760 isillustratively shown in FIG. 17.

FIG. 15 is a flowchart showing in further detail the photo system“interfaces with a user device to input a new photo” of subroutine 710that can be called upon or invoked from the processing of FIG. 14. Asshown, the process starts in step 710 and passes onto step 711. In step711, the system waits for a request from a user device to input a photo.If no is rendered, then the process passes onto step 712. In step 712,the system continues to wait for user input.

On the other hand, a yes determination may be rendered in the processingof step 711, indicating that the system has indeed received a requestfrom a user device to input a photo. Accordingly, the process passesonto step 713. In step 713, the system confirms identity of theparticular user by inputting credentials from the user, confirming thatcredentials have already been input from the user, and/or authenticatingthe user device in some manner Any suitable authentication mechanism,arrangement, or technology can be utilized so as to allow the system toconfirm identity of the user device and/or human user. For example,biometrics can be utilized so as to authenticate the user device and/orhuman user. After step 713, the process passes onto step 714.

In step 714, the system confirms that the photo includes and/or isassociated with metadata identifying the user and/or user device thattook the photo. Then, the process passes onto step 715.

In step 715, the system confirms that the photo includes and/or isassociated with metadata representing date and time that the photo wastaken. Then, in step 716, the system confirms that the photo includesand/or is associated with metadata representing location that the photowas taken. After step 716, the process passes onto step 720.

In step 720, the system determines whether or not all requirements havebeen satisfied so as to input the photo into the system. If no, then theprocess passes onto step 723. In step 723, the system outputs acommunication to the user that the photo, which the user submitted, isnot accepted. Such communication can provide basis for not accepting thephoto, so as to be helpful to the user.

If the processing determines that all requirements have been satisfiedto input the photo into the system, in step 720 of FIG. 15, then a yesis rendered in step 720. Accordingly, the processing passes onto step721. In step 721, the system interfaces with the user to inputattributes of the photo. In such processing, subroutine 730 of FIG. 16can be called upon or invoked. Accordingly, it should be appreciatedthat the system can interface with a user so as to input attributes ofthe photo subsequent to input of the photo (step 721 of FIG. 15) orindependently of input of the photo (step 702 of FIG. 14), i.e. at somelater time relative to input of the photo itself.

After step 721 of FIG. 15, the process passes onto step 722. In step722, the system places the photo, with metadata, in queue forprocessing. Accordingly, with the processing of step 722, the processingof FIG. 15 can be terminated. Once photo(s) are identified or observedas being in queue, the system can invoke or call upon the processing ofstep 521 of FIG. 6.

Accordingly, in the processing of steps 713, 714, 750, 716, varioussteps can be performed so as to determine if the photo possessesrequired attributes or metadata so as to be processed by the system 100.As reflected at 621′ of FIG. 15, such processing can be complementary tothe processing performed in FIG. 6.

FIG. 16 is a flowchart showing in further detail the “PS interfaces witha user to input attributes of photo” subroutine 730 as called from theprocessing of FIG. 15. The process of FIG. 16 is initiated and theprocessing passes to step 731. In step 731, the PS waits for a requestfrom the user via either of step 740 or step 750. In step 740, the PSmonitors for an input request from the user to associate “location type”with the photo. In step 750, the PS monitors for an input request fromthe user to perform site association of the photo. For example, the“wait” processing of FIG. 16 can include the PS waiting for a user tolog on or sign into the system, i.e. the PS (photo system)—and engagewith the PS so as to render a yes in step 740 or step 750.

In the processing of step 731, as reflected at 731′, the PS caninterface with the user to associate other or additional data with theparticular photo that is being processed. Such data, which is thenassociated with the photo, can then be used in various processing. Forexample, the additional data associated or appended to the photo can beused by the PS to perform searching based on a user query, i.e. based ona user search. The additional data can be used to determine if a patchcan be elevated to the disposition of a spot.

With reference to step 740, upon a request being received in step 740such that a “yes” is rendered in the processing, the process passes tostep 741. In step 741, the PS presents options to the user so that theuser can select a particular location type, for example. That is, in theprocessing of step 741, the user can associate a photo with a locationtype. For example, the PS can interface with the user so as to present aphoto to the user. The user might select the photo in some suitable waysuch as from an index of photos, a listing of photos, or in some othermanner Once a particular photo is selected, the user may be presentedwith a list of possible location types which may be associated with theparticular photo. For example, “location types” that are presented tothe user (as an option to associate with a photo) can include places,events, things, or virtual. Other location types can be provided as maybe desired. The location type “places” can provide the user the abilityto associate a photo with a particular place. The location type “events”can provide the user the ability to associate a photo with a particularevent. The location type “things” can provide the user the ability toassociate a photo with a particular thing. The location type “virtual”can provide the user the ability to associate a photo with a virtualconcept, such as to provide an association of a photo with a game basedevent, for example.

With reference to step 750, the CP can determine that a request wasindeed received from a user to perform site association of a photo.Accordingly, a yes is rendered in step 750. The processing then passesto step 751. In step 751, the PS retrieves location of the photo. Forexample, the PS may retrieve the location of the photo from metadataassociated with the photo. Then, the process passes onto step 752. Instep 752, the PS identifies sites that are associated with the locationof the photo, i.e. the location that was retrieved in step 751. Then,the process passes onto step 753. In step 753, the PS associates thephoto with the identified sites. For example, one “site” might be NewYork City. Another “site” might be Times Square. Accordingly, a phototaken in Times Square can be associated (in step 753) with both theTimes Square site and the New York City site. As reflected in step 753,popularity of the sites will be increased by the addition of the phototo that site, in accordance with at least some embodiments. As reflectedat 754 of FIG. 16, the virtual container that the photo is associatedwith can be performed through separate processing vis-à-vis processingof step 751-753. Relatedly, a site can be composed of a plurality ofspots.

FIG. 17 is a flowchart showing in further detail the “PS interfaces witha user device to perform photo user processing subroutine 760 of FIG.14. The process is initiated and passes to step 761. In step 761,various processing can be performed in step 762, 763, 764, and 765. Suchprocessing can be requested or invoked through user interface.

In step 763 of FIG. 17, the PS can interface with the user to performrequested processing for the user. For example, the PS can interfacewith the user to perform “spots around me” or “spots near me” processingfor the user. Such processing can also be described as “Spotz Around Me”processing. The term “spotz” can be used interchangeably with the term“spots” so as to reflect the novel processing of the disclosure.Additionally, the term “ShotSpotz” can be used to mean, be a part of, orinclude the photo system 100, in accordance with at least one embodimentof the disclosed subject matter. In such processing of FIG. 17, the PScan retrieve or input the geographical location of the user device so asto identify spots that are proximate to the user. The proximity can bedetermined based on predetermined thresholds. That is, settings can beprovided that can control whether “proximate” means within 1 mile of theuser, 10 miles of the user, or 100 miles of the user, for example. Theprocessing of step 763 can also include “find a spot” processing. Infind a spot processing, the user can enter search criteria or searchterms that contain criteria of what the user is looking for either in aphoto or in a spot. For example, a GUI 1800 as shown in FIG. 18 can beutilized so as to input search criteria from the user. In regard to“find a spot” processing—such processing can include or be associatedwith planning, planning a trip, organizing a plurality of spots, savinga collection of spots, retrieving one or more spots, and relatedprocessing and functionality.

Additionally, the processing of step 763 can include “upload a photo”processing. In such processing, a photo can be uploaded from a userdevice of the user. The photo can then be processed as otherwisedescribed herein. Additionally, step 763 can include the option “use thecamera”. With such option, the camera of the user device can beactivated. FIG. 20 illustrates a GUI 2000 that can be utilized so as tolaunch or invoke the processing of step 763 (FIG. 17).

In step 762 of FIG. 17, the PS can interface with the user to inputsearch filters to apply in performing search for photos. Such searchfilters can include such items as usage, lens, time of day, season, andcrowd size. The processing of step 762 can provide functionality toallow a user to specify the things that the user wants to see, where todrink e.g., provide a filter for image types, filter an image based onmetadata or attributes associated with the image, and/or provide otherfunctionality. FIG. 21 illustrates a GUI 2100 that can be utilized so asto interface with the user so as to input selection of search filters.For example, a particular search filter option or options can beprovided via a drop-down menu. For example, a usage option can beprovided via which the user chooses a particular usage option, whichmight be Street, urban, or night. The lens option can provide the user,searching for a particular photo, to request photos that have been takenwith a particular type of camera, such as a wide lens camera or asuperwide lens camera. For example, an option can be provided in whichthe user indicates he or she would like to search for photos that weretaken in a particular season of the year.

In accordance with at least one embodiment of the invention, “spot”generation can be correlated with the search filter options provided inthe GUI 2100. For example, a patch can be processed to determine if thepatch is associated with at least 20 pictures that were taken in thesummer. If such patch does indeed include 20 pictures that were taken inthe summer, then that patch would be deemed (by the photo system (PS))to be a “spot” for that particular search criteria. More generallyspeaking, a particular area, such as a patch, can be assessed todetermine if such area possesses density of photos with certainattributes, such as usage, lens, time of day, season, or crowd size. Anarea that does indeed possess density of a particular attribute can thenbe deemed a spot for that attribute. The user can then search for spotswith such attribute, i.e. as shown in the GUI of FIG. 21.

FIG. 17 can also include the processing of step 764. In step 764, the PSinterfaces with the user to input user location or user device locationto apply in performing search for photos. For example, the PS can inputthe user device location in step 764. Then, additional processing can berequested by the user that uses such input user device location. Forexample, the “spots around me” processing can be performed after the PSinputs user device location in step 764.

FIG. 17 can also include the processing of step 765. In step 765, the PSperforms “photo info” processing. FIG. 18 is a GUI 1800 that illustratessuch processing. Further details of the GUI 1800 are described below.

In accordance with an embodiment, the PS can identify when the user hasinput search criteria and has selected that the PS should perform asearch based on such search criteria. The search criteria can be a widevariety of criteria such as spots around the user, spots having acertain photo density, spots having photos of a particular type, spotshaving photos of a particular attribute, spots that are associated witha particular site, and other criteria as may be desired. Accordingly,once the PS identifies that the user has interfaced (with the PS) so asto provide both search criteria and a request to perform the search,then the process passes onto step 766. In step 766, the PS outputs theresults of the search to the user device. The results of the search canbe one or more spots, from which the user can select, which match theinput criteria. The results of the search can be one or more photos thatmatch the input criteria. The results of the search can be one or moresites that match the input criteria. Additional processing can then beprovided by the PS.

That is, in step 767, the PS can interface with the user device todetermine if the user wants to refine the search criteria. If yes, thenthe process passes back to step 761. Processing then continues asdescribed above. In step 768, the PS can interface with the user todetermine if the user wants more information regarding an identifiedspot, for example. More specifically, the processing of step 768 caninclude a situation in which the user is presented with a spot or spotsthat matches the search criteria input by the user. Upon being presentedwith spots that match the search criteria, the user can select aparticular spot. Upon selection of the particular spot, the PS canprovide additional information to the user regarding the selected spot.FIG. 28 is a GUI 2800 that can be presented to the user—to provide acollection of spots that satisfy search criteria of the user. Uponselection of a particular spot in the GUI 2800, of FIG. 28, variousinformation regarding the selected spot can be presented. Details of aselected spot that can be presented to the user includes number ofphotos in the spot, various attributes of those photos, the types ofphotos in the particular spot, attributes of users who took the photosthat are in a particular spot, and various other information regardingthe spot and photos that are associated with the spot.

In the processing of step 768, a yes request can be received.Accordingly, the process passes onto step 769. In step 769, the PSoutputs further data, regarding the selected spot, to the user device.

As described above, FIG. 18 is a GUI that illustrates aspects of “photoinfo” processing. The GUI 1800 can be utilized or a variation of the GUI1800, to perform a variety of processing. The GUI 1800 can be presentedto the user in various operating situations. For example, the GUI 1800can be presented to the user in conjunction with inputting a photo fromthe user. For example, the GUI 1800 can be utilized to provide theprocessing of step 741 of FIG. 16. The GUI 1800 can include a pluralityof criteria 1801. For example, the criteria 1801 can constitute the“location type” of step 741 (FIG. 16). Each criteria can then beassociated with a ranking 1802. The ranking 1802, for each criteria1801, can be selected by the user so as to input data regardingattributes of the particular photo (that is being input or uploaded fromthe user). For example, in the example GUI 1800, the user has selected aparticular ranking 1810 that corresponds to a “drink” location type. Theuser can tap such item 1810. Upon tapping such item 1810, the PS canhighlight the item, bold the item, or provide some other change inappearance of the item so that the user can see that such item has beenselected. The user can select any number of items in the GUI 1800.Additionally, the GUI 1800 can be provided with a button 1820. Thebutton 1800 can take the user to additional GUIs or user interfacemechanisms by which the user can input additional information regardingthe particular photo. Accordingly, the GUI 1800 provides a quick andefficient way for the PS to input information regarding a photo from theuser. Upon a user completing his or her selection in the GUI 1800, theuser can tap the button 1840 so as to indicate to the PS that the userhas completed selection—and that the PS can process the uploaded orinput photo based on the user's selections. Accordingly, the GUI 1800 ofFIG. 18 can be utilized in conjunction with a user uploading a photo—toprovide the user with a mechanism to input attributes of such uploadedphoto. However, the GUI 1800 can also be utilized to perform otherprocessing. That is, the GUI 1800 can be presented to the user so thatthe PS can input search criteria from the user. The user can makeselections in the “matrix” of the GUI 1800 as may be desired. The PS canthen perform a search based on the input criteria. In such processing,the button 1820 can be utilized by the user so as to allow the user toinput more detailed search criteria information. In such processing, thebutton 1840 can be selected by the user upon the user completing his orher selection(s), for example ranking 1810, of the various items in theGUI 1800. Thus, upon the user tapping the button 1840, the PS canperform the requested search.

FIG. 19 shows a GUI 1900. The GUI 1900 can be presented to a user orpotential user in conjunction with the user signing on or logging in tothe PS (photo system). The GUI 1900 can include a login option. The GUI1900 can include a login via Facebook option. The GUI 1900 can alsoinclude a create account option, i.e. in the situation that the user hasnot yet created an account in the PS. It should be appreciated theoptions shown in the GUI 1900 are illustrative. Additional options ormechanisms can be provided so as to input credentials from the user andallow the user access to his or her account.

Features of FIG. 20 are described above. In accordance with at least oneembodiment of the disclosure, the GUI 2000 of FIG. 20 can provide a mainlanding page. That is, the user might be presented with the GUI 2000upon first logging on to or in 2 the system.

As described above, a processing option provided by the PS can include“spots around me” or what might be described as “spots near me”. In suchprocessing option, the PS can generate a GUI 2200 such as shown in FIG.22. The GUI 2200 can include first indicia 2201 that reflects userlocation or user device location. The GUI 2200 can also include secondindicia 2210 that reflects “spots” around the user that the PS hasidentified. For example, the user might hover his or her cursor over aparticular indicia 2210 so as to invoke the system to present additionalinformation regarding the particular spot that is thereby selected. Auser can select a particular spot in some manner, such as by clickingthe particular spot, as represented by indicia 2210. In clicking aparticular spot, the PS can present the user with various photos 2220that are contained in the selected spot. The PS can interface with theuser so as to allow the user to “flip through” the various presentedphotos 2220.

As described herein, the PS can perform various processing related to aspot. A spot can be generated based on a particular area, such as apatch, having sufficient photo density. Relatedly, a plurality of spotscan be collectively form a “site”. In such processing, the PS cangenerate a GUI 2300 such as shown in FIG. 23. The GUI 2300 can includefirst indicia 2301 that reflects user location or user device location.The GUI 2300 can also include second indicia 2310 that reflects “sites”around the user—that the PS has identified. The user might hover his orher cursor over a particular indicia 2310 so as to invoke the system topresent additional information regarding the particular site that isthereby selected. A user can select a particular site in some manner,such as by clicking. In clicking the particular site, the PS can presentthe user with various photos 2320 that are contained in the particularselected site. The PS can interface with the user so as to allow theuser to “flip through” the various presented photos 2320 that areassociated with the selected site.

In accordance with a further aspect of the disclosure, FIG. 24 shows aGUI 2400 that illustrates “spots around me” functionality. The GUI 2400can provide information to the user regarding spots around the user—andmore specifically provide a map view of spots around the user. A usercan select a particular spot, for example as represented by indicia2450. Once selected, information regarding the particular spot can bedisplayed to the user in a display box 2460. A distance between the userand the spot can be displayed. For example, such distance might be basedon a center point of the particular spot. As described above, a “spot”can be an area, such as a patch, that has attained a threshold densityof photos or that has attained a threshold density of photos of aparticular type or attribute, for example. The display box 2460 can alsoinclude additional information. Such additional information can includesites that are associated with the particular selected spot. The usermight select a particular site so as to result in the PS to display yetfurther information regarding the particular site.

FIG. 25 shows an additional GUI 2500 that can be presented to the userto provide additional information to the user regarding spots around theuser or user device. The selection of photos can be presented based onvarious options or criteria. For example, a representative photo foreach spot can be presented to the user. For example, all photos from aparticular spot or spots can be presented to the user. The user can beprovided the ability to select a photo. Selection of the photo canresult in additional information being displayed to the user, such asparticulars of the spot to which the photo is associated. Suchadditional information is illustrated by display box 2650 in the GUI2600 of FIG. 26. Such data can include a distance that the user is fromthe selected spot or the selected photo. Such data can include sitesthat are associated with the selected spot or the selected photo.

FIG. 27 shows a GUI 2700 that can be presented to the user via asuitable menu selection. The GUI 2700 can include various optionsincluding about, my account, my spots, following, and preferences. Theabout option can provide various information about the user. The myaccount option can provide various information to the user regarding heraccount, as well as functionality so that the user can change attributesof their account. For example, the my account option might provide theuser with the ability to change a phone number associated with heraccount. The my spots option can provide various information regardingthe spots, i.e. that can be described as “Spotz”, that are associatedwith the user account. For example, the my spots option can provide theuser with details regarding spots to which the user has contributedphotos. The my spots option can provide the user functionality so thatthe user can opt to receive updates regarding particular spots, i.e.favorite spots.

Additionally, the GUI 2700 can include a “following” option. Thefollowing option can provide functionality by which the user can selectspots that the user desires to “follow”. For example, a user following aspot can mean that the system can identify any changes or updates to thefollowed spot. For example, if photos are added to the particular spot,then the user (who is following the spot) can be notified of such addedphotos. Additionally, the “following” functionality can include variousother options. For example, the following functionality can include anassociation between the particular user and a second user. For example,a first user might follow a second user so as to be updated regardingwhere the second user has taken photos, spots with which the second userhas engaged with, or other information. The PS can interface with eachof the involved users so as to input authorization and/or acceptance toshare related data.

As described above, FIG. 28 shows a GUI 2800 that can provide variousinformation regarding one or more spots. In particular, FIG. 28 canprovide the user access to photos associated with a particular spot. Asdescribed above, FIG. 18 is a GUI (graphical user interface) 1800 thatillustrates aspects of “photo info” processing. The GUI 1800 can providean interface by which the PS can input various information regarding aphoto, a group of photos, a collection of photos, a spot, or a site, forexample. As described above, the GUI 1800 can also include the button1820. The button 1820 can be selected by the user so as to inputadditional information. Relatedly, FIG. 30 shows a GUI 3000 that can bedisplayed as a result of the user tapping or selecting the button 1820.In other words, the GUI 3000 can be presented to the user so as toprovide the user the ability to add additional information above andbeyond that input via GUI 1800. The GUI 3000 can be presented to theuser via suitable menu option. The GUI 3000 might be selected by theuser tapping the criteria or location type “do” 1801 in the GUI 1800 ofFIG. 18. The GUI 3000 allows the user to input additional particularsregarding the “do” location type. For example, if an input photo relatesto activities associated with a museum, then the user might select theappropriate item 3060 as illustrated in FIG. 30. The GUI 3000 caninclude dialogue box 3099 into which a user can input comments, i.e.text, regarding the user's selection in the GUI 3000, one or moreassociated photos, and/or the user, for example.

FIG. 29 is a further GUI 2900 in accordance with principles of thedisclosed subject matter. The GUI 2900 can be presented to the user inconnection with either tagging a photo that is to be uploaded to thephoto system or in connection with searching for a particular type ofphoto or spots having a particular type of photo. Using the GUI 2900,the user can specify whether the user wants to tag a particular photo assee, do, drink, eat, or stay, for example—or to search for a photohaving such attributes.

FIG. 31 illustrates a further GUI 3100 that can be generated by the PSand presented to the user. The further GUI 3100 allows the user to inputadditional information regarding a “drink” location type. The GUI 3100can include dialogue box 3199 into which a user can input comments, i.e.text, regarding the user's selection in the GUI 3100, one or moreassociated photos, and/or the user, for example. FIG. 32 illustrates afurther GUI 3200 that can be generated by the PS and presented to theuser. The further GUI 3200 allows the user to input additionalinformation regarding an “eat” location type. The GUI 3200 can includedialogue box 3299 into which a user can input comments, i.e. text,regarding the user's selection in the GUI 3200, one or more associatedphotos, and/or the user, for example. FIG. 33 illustrates a further GUI3300 that can be generated by the PS and presented to the user. Thefurther GUI 3300 allows the user to input additional informationregarding a “stay” location type. The GUI 3300 can include dialogue box3399 into which a user can input comments, i.e. text, regarding theuser's selection in the GUI 3300, one or more associated photos, and/orthe user, for example

Hereinafter further features of the systems and methods of thedisclosure will be described.

As described above, a particular area can achieve a predetermineddensity of photos so that the area can be elevated to the status of aspot. The predetermined density of photos can include a determination ofhow many photos of any type are disposed in the particular area. Thepredetermined density of photos can include a determination of how manyphotos of a particular type are disposed in a particular area. Inresponse to a search query by a user, search results can be providedbased on whether an area has or has not attained the status of a spot.Further functionality can be provided so as to distinguish betweendifferent spots. For example, spots can be ranked so as to be comparedwith other spots. For example, a predetermined threshold to attain spotstatus can be 20 photos in a particular area, such as in a particularpatch. However one spot can include 21 photos. Another spot can include55 photos. Accordingly, functionality can be provided so as todifferentiate the relevancy of such 2 different spots. For example, datacan be provided to the user, in response to a search query, so as toadvise the user of such different density in spots. For example, a spotcan be ranked so as to be able to be compared with other spots.Additionally, the criteria or thresholds used to determine if density ofan area is sufficient to deem the area a “spot” can depend on variouscriteria. For example, in a highly populated area, the threshold toelevate an area to a spot can be different than the threshold (toelevate an area to a spot) in a very rural area. Thus, in New York City,a patch might be required to have 50 photos associated with a patch soas to attain spot status. On the other hand, a patch in a rural area mayonly be required to have 10 photos associated with such patch so as toattain spot status. Further, patches in respective regions, such asrural versus urban, can be of different size, in accordance with atleast one embodiment of the disclosed subject matter.

Relatedly, various attributes of a particular photo can be used so as todetermine whether the photo should or should not count toward elevatinga particular area to a spot. For example, date data or metadata that isassociated with a particular photo can dictate whether the photo shouldbe counted towards elevating an area to spot status. For example, for aparticular area, if the date of the photo is more than 6 weeks old, thenthe photo might not count. In a high-traffic area, such threshold datemight be much more recent than a more rural area. Various factors can beconsidered in determining such threshold date for whether a photo is oris not counted towards spot status. Additionally, date “Windows” can beutilized. For example, a particular event may have occurred over aparticular week. Accordingly, only photos that bear a date of that weekmight be deemed to count towards spot status. Additionally, attributesrelating to upload of the photo can also be taken into account inwhether a photo should or should not be counted towards spot status. Forexample, if a photo is taken at a particular location, in a particulararea, and uploaded within 5 minutes—then such photo may be deemed a“recent” or “live” photo. In such processing, both data regarding whenthe photo was actually taken and when the photo was uploaded can beused. For example, if the photo was not uploaded until after somepredetermined time, such as two days, then the photo might not becounted towards spot status. Accordingly, predetermined thresholds canbe used that relate to when a photo was taken and when the photo wasuploaded to the photo system, for example.

As described herein, a spot can be generated in any of a variety ofmanners. A spot can be generated based on pure number of photos within aparticular area. A spot can be generated based on number of photos of aparticular type within a particular area. Thus, a single geographicalarea can be associated with a plurality of spots that correspond to thatarea. For example, a particular area may be deemed a spot based on sucharea including 20 photos that have been tagged as location type “drink”.That same area may be deemed a spot based on such area including 20photos that have been tagged as location type “eat”. Additionally, thatsame area may be deemed a spot based on such area including a totalnumber of 30 photos, i.e. in the situation that a threshold number ofphotos to attain spot status might be 25. Accordingly, the PS providesthe ability for a user to search or assess “spots” in a variety ofdifferent manners. Such different manners might be described asdifferent “lenses” through which the user might look to assess detailsof a particular area. Relatedly, functionality provided by the PS mayallow for the observation of correlation, or lack thereof, betweenattributes of spots associated with a particular area. For example, aparticular “area X” may have gained spot status by virtue of asufficient number of photos being tagged as location type “eat”. Indeed,the number of photos may have far exceeded the threshold to attain spotstatus. However, that same area X may not have attained spot statusbased on number of photos being tagged as location type “drink”.Accordingly, such disparity can be observed. In such situation, it maybe the case, for some reason, that a correlation is expected betweendrink location type and location type. However, in this example, suchcorrelation is not observed. Accordingly, such disparity may be flaggedand appropriate action taken and/or appropriate research performed so asto determine the reason behind such disparity. Appropriate action can betaken in some automated manner by the photo system.

Relatedly, the upload or submission of a photo associated with aparticular area may indeed constitute a “vote” by the user for thatarea. As the user uploads a further photo associated with an area, thatphoto constitutes a further vote for the area. Such functionality can bedescribed as “your picture is your vote” or such functionality can bedescribed as “the picture is your vote”.

In accordance with principles of the disclosed subject matter, asubmitted photo can relate to various aspects of ranking and popularity.Popularity can include or relate to volume of submitted photos and/or apreference strength as determined by submitted photos and can beflexible for location type, etc. Therefore, a submitted photo by a usercan led to related ranking processing and attributes, such as theranking of a spot or area. Accordingly, a user's photo can constitute avote and that vote can vary by location and/or purpose. The viewpoint ofa “spot” can be presented in a variety of methods, whether by volumeranking, user following strength, affinity group, etc. Such processingcan be described as an “assessment” that can include assessment of“ratings” based upon varying ranking viewpoints, different lenses,lenses of different rankings and dominant lens, for example.

To describe further, processing can be performed that provides an“assessment” of a spot or other area. Such “assessment” can includeverification of attributes of an area, and such attributes can includepopularity of an area. Assessment can include performing processing toprovide multiple viewpoints of the same thing, such as the popularity ofa coffee house based on input photos that are input from two differentaffinity groups. Assessment can reveal differing or divergent viewpointsof an area. Assessment can include the aggregation or analysis of anarea from different perspectives or from different lenses or fromdifferent affinity groups, i.e. based on respective data that is inputfrom such different affinity groups. Assessment can reveal both (1)validation of an attribute of an area and/or (2) identification ofdivergence of opinion regarding an attribute of an area.

For example, some users might be associated with a first affinity groupand some users might be associated with a second affinity group.Association of a particular user to an affinity group can be based onuser interaction and/or attributes of the user. For example, the usermight input data to the system indicating that the user is a “hiker” ora “climber”. A GUI might be presented to the user via which the userinputs such data. Also, attributes of a user might dictate an affinitygroup to which the user will be associated, i.e. for example, the systemmight identify locations that the user frequents and, based thereon, tagthe user as a hiker or a climber.

In one scenario, the hiker affinity group might collectively submitphotos, which can be described as votes, so as to deem a particularrestaurant popular. The climber affinity group might also collectivelysubmit photos so as to deem the same restaurant popular. Based on suchdata that is input by the system, the system can assign a level ofvalidation to such restaurant as truly being popular, i.e. since therewas correlation between the hiker group and the climber group.

In a different scenario, the hiker affinity group might collectivelysubmit photos, which can be described as votes, so as to deem aparticular restaurant popular. The climber affinity group might alsocollectively submit photos so as to deem the same restaurant NOTpopular. Based on such data that is input by the system, the system canassign a level of divergence or an indication of divergence to suchrestaurant as questionably being popular, i.e. since there was NOTcorrelation between the hiker group and the climber group.

Accordingly, “assessment” processing of the disclosure can (1) determinepopularity of an area, (2) determine unpopularity of an area, and/oridentify divergent perspectives of different affinity groups, forexample. Assessment processing of the disclosure can include (1)determination of a popularity of an area, (2) validation of a popularityof an area, (3) substantiation of a popularity of an area, and/or (4)identify divergence (of popularity or unpopularity) amongst differentviewpoints or amongst different affinity groups.

Such “assessment” might also be described as a “triangulation” of a spotor area or might also be described as including “triangulation” or“validation” of a spot or area.

In accordance with principles of the disclosed subject matter and asdescribed above, the world or planet can be divided into areas inaccordance with principles of the disclosed subject matter. The areascan include 6 levels in accordance with one embodiment of the disclosedsubject matter. The areas can be divided in a hierarchical manner—witheach area of a particular level being divided into subareas. Such mightbe in the form of a parent and child interrelationship as describedabove. However, the disclosure is not limited to such particulars. Forexample, instead of the planet being broken down into areas andsubareas, a venue might be broken into areas. For example, the venue ofa tradeshow might be an area to be broken down, i.e. such that the venueof the tradeshow is analogous to the planet. The venue of a tradeshowmight be broken down into different levels of areas as desired, such as4 levels. The lowest level might be termed a “patch” akin to the patchdescribed above. Each of the patches at the tradeshow might correspondto a respective booth. As each booth receives a threshold number ofphotos, that booth/patch is elevated to be a “spot”. Each photo can beviewed as a vote. The systems and methods of the disclosure can beapplied in many other uses. For example, the systems and methods of thedisclosure can be applied to zip codes and/or voting wards.

The systems and methods of the disclosure can also include functionalityrelated to monitoring or censoring that can be performed by the photosystem (PS) or by users of the PS. For example, such censoring caninclude a user censoring for inappropriate photo content or othercontent (for example explicit content or violence) being uploaded.Another example of censoring can include a user censoring for photosthat have been tagged with an inaccurate or inappropriate location type.For example, a user might observe a number of photos that have beentagged as location type “places to eat”. However, upon review of suchphotos, the photos may not in any way be related to restaurants oreating. Accordingly, the user may interface with the system so as tode-tag or un-tag the particular photo or photos. In at least someembodiments, such un-tagging can result in the photo immediately beingremoved from such “places to eat” status. In other embodiments, anadministration person or functionality may be required prior to thephoto being removed or un-tagged from such “places to eat” status. Insome embodiments, a user can be provided with the ability to quarantinea photo or a group of photos.

Relatedly, functionality can be provided so as to censor the censoror,i.e. the user doing the censoring. Such functionality can be provided bythe photo system (PS) assessing correlations between various data ordata sets. For example, a user that is observed as censoring outside orin excess of a norm can be scrutinized or constrained in some manner.For example, a user can be constrained based on some predeterminedthreshold(s). For example, if a user is observed by the system to de-tagor un-tag allegedly inappropriate photos at twice average rate—suchmight constitute a threshold. Based on exceeding such threshold, auser's ability to de-tag or un-tag additional photos might be disabled.Such disabling might be performed in some automated manner by the photosystem. In accordance with principles of the disclosed subject matter,such a user can be identified as an outlier, based on predeterminedcriteria and/or thresholds, and as a result, the user's censoringabilities be constrained or disabled in some manner Systems and methodsare provided to process a digital photo. An apparatus to process digitalphotos can include a tangibly embodied computer processor (CP) and atangibly embodied database, the CP implementing instructions on anon-transitory computer medium disposed in the database, and thedatabase in communication with the CP. The apparatus can include (A) acommunication portion for providing communication between the CP and anelectronic user device; (B) the database that includes a non-transitorycomputer medium, and the database including the instructions, and (C) acascading framework that includes framework areas, and the frameworkareas include: first level areas, and each of the first level areasdivided into second level areas, the second level areas being dividedinto third level areas; and (D) the CP. The CP can perform processingincluding: (a) inputting a photo from the user device, and the photoincluding geographic data that represents a photo location at which thephoto item was generated; (b) comparing the first level area, of thefirst level areas, in which the photo location is located andassociating a first level area identifier to the photo as part of thephoto data; (c) comparing the photo location with the second level areasto determine a second level area in which the photo location is locatedand associating a second level area identifier to the photo as part ofthe photo data; (d) comparing the photo location with the third levelareas to determine a matching third level area in which the photolocation is located and associating a third level area identifier to thephoto as part of the photo data; (e) assigning the photo to the matchingthird level area; and (f) performing photo processing, and the photoprocessing including aggregating a photo count of the matching thirdlevel area.

In accordance with principles of the disclosed subject matter, thedisclosure provides systems and methods to perform geographicidentification of an area combined with using a photo, which isassociated with the area, as a vote for one or more popularitydeterminations of the geographic area. The geographic area can be usedfor a variety of other purposes. The geographic area and/or a photoassociated with the geographic area can be tagged so as to associatecontent or attributes to the geographic area and/or to the photo.

Hereinafter, further aspects of the systems and methods of thedisclosure will be described.

FIG. 34 is a high level flowchart showing additional processing of thedisclosure in accordance, with principles of the disclosed subjectmatter. The additional processing relates to further aspects ofsegmentation, association of a photo to a patch, visual display ofinformation, and various related features. Details are described below.

As shown, the high level processing can begin in step 3400 whichreflects that the photo system (PS) performs photo processing. Onceinitiated or launched, the processing passes onto step 3401. In step3401, various additional processing can be performed. Acronyms describedfor reference, as reflected at 3400′ in FIG. 34, include CP—computerprocessor; VA—viewport area; SB—search bounds; LL—longitude Latitude;and UAI—unique area identifier.

The processing of step 3401 can include step 3500. In step 3500, theprocessor or computer processor (CP) performs area segmentationprocessing. In such processing, an area such as the world or globe issegmented into identifiable areas. Further details are described withreference to FIG. 35. The processing of step 3401 can also includes step3600 and step 3900. In step 3600, the processor associates a photo to apatch. In other words, the processor associates a photo that is inputinto the system into a designated area or framework of the system.Further details are described with reference to FIG. 36.

The processing can also include step 3900. In step 3900, the processorprocesses a user request for display of a “visual area”, i.e. that canbe described as a viewport area (VA) on a user device (UD). The userdevice can include a cell phone. Further details are described belowwith reference to FIG. 39. As reflected at 3400″, various additionalprocessing can be performed by the CP in conjunction with the particularprocessing shown in FIG. 34. Such additional processing is otherwisedescribed herein.

FIG. 35 is a flowchart showing details of “processing is performed toassign area identifier and identify boundaries of an area” of step 3500of FIG. 34, in accordance with principles of the disclosed subjectmatter. As shown, the process starts in step 3500. The processing ofFIG. 35 or portions of such processing can be used in lieu of theprocessing of FIGS. 3 and 4 described above, in accordance with at leastsome embodiments of the disclosed subject matter. The processing of FIG.35 can be used in combination with features of the processing of FIGS. 3and 4, as may be desired. In this illustrative embodiment of thedisclosure, the processing of FIG. 35 can be used to establish aframework of “remote” areas. That is, in other words, what are describedas “remote” areas can be generated that include both identifiers andboundaries of each respective remote area that is generated.Accordingly, a framework can be generated. Subsequent processing canthen build on such initial framework.

After the processing starts in step 3500 of FIG. 35, the process passesonto step 3501. In step 3501, the CP can retrieve the start or initialanchor point for a first area to demarcate. For example, anchor pointscan be identified by latitude and longitude where a first anchor pointcan be 0 latitude and 0 longitude, i.e. off the East Coast of Africa inthe Atlantic Ocean. However, the initial anchor point can be anylocation as desired. Then, the process passes onto step 3502.

In step 3502, the CP retrieves an initial or start unique areaidentifier (UAI). Further details of the UAI are described below withreference to FIG. 37. After step 3502, the process passes onto step3503. In step 3503, the CP assigns a UAI to the current anchor point orother identifying reference point or attribute of the particular area.Also in step 3503, the CP assigns boundaries to the current anchorpoint, which corresponds to the current UAI. The assignment ofboundaries is described further below.

Then, the process passes to step 3504. In step 3504, the CP retrieves anadvance parameter for the current level, i.e. in the present example the“remote” level is the current level. In this example, each remote areais 100 miles×100 miles. Accordingly, the processing can advance or move100 miles east of a current anchor point so as to advance to the nextanchor point. That is, after step 3504, in which the advance parameteris retrieved, the process passes onto step 3505. In step 3505, based onthe X-coordinate advance parameters or value, the CP identifies the nextproposed anchor point of the next area (for the current level) and in acurrent row. Accordingly, the processing of step 3505 reflects that“remote” areas can be carved out or demarcated by going east around theglobe or world. As described above, once an anchor point for aparticular remote area is identified, the CP can then advance 100 milesto the east so as to identify the next anchor point for the next area.It should be appreciated that areas can be generated, i.e. “carved out,”in other directions as may be desired.

After step 3505, with a next potential anchor point identified, theprocess passes onto step 3510. In step 3510, the CP determines based onGPS (global positioning system) location (or longitude/latitude) of thecurrent area, whether demarcating or staking out the remote areas hasbeen completed. In other words, has the globe or world (or some otherarea that has been designated for segmentation) been fully demarcated orcarved out into discrete “remote” areas. For example, such processingcan compare GPS locations of areas that have been carved out versus GPSdata of the entire globe. If the entire globe is populated with carvedout areas, then the determination of step 3510 renders a yes.Alternatively, the GPS locations of areas that have been carved out or“staked out” can be compared to a specific area that is desired to be“staked out”. If the complete area desired to be staked out is fullypopulated with areas, in this illustrative example “remote” areas, thena “yes” would be rendered in the processing of step 3510. On the otherhand, a “no” may be rendered in step 3510.

If a “no” is rendered in step 3510, the process then passes onto step3511. In step 3511, the CP determines, based on GPS location of thecurrent area, whether the current “row” of areas is completed. That is,the processing can determine whether the GPS location of the currentarea being processed is approaching a GPS location of a previouslystaked out area. For example, if a new anchor point is identified—andsuch new anchor point is identified to be within 100 miles of apreviously identified anchor point—than the processor can determine thatthe particular “row” circling the globe has been completed. Accordingly,a “yes” can be rendered in the processing of step 3511. The process thenpasses onto step 3512.

In step 3512, the CP drops down, i.e. since in this example thesegmentation is advancing in a southern direction, to “stake out” thenext row of “remote” areas. The amount of the CP drops down can bedictated by a Y-coordinate advance value or parameter. In this example,the described “remote” areas are 100 miles×100 miles. Accordingly, theY-coordinate advance value is the same as the X-coordinate advancevalue, i.e. 100 miles, in this example. After step 3512, the processpasses onto step 3513A.

On the other hand, a “no” may be rendered in the determination of step3511. Such “no” determination indicates that there are still additional“remote” areas that are to be carved out or demarcated in the particularrow of areas. Accordingly, the next remote area can be determined byadvancing in eastern direction according to the X-coordinate advancevalue. In this example, the X-coordinate advance value can be 100 miles.After step 3511, upon a no being rendered, the process passes to step3513A.

Accordingly, step 3511 or step 312 are reflective that a proposed anchorpoint has been determined that can be associated with or identify afurther area. If the further anchor point “runs up against” a previouslyidentified anchor point or other row ending identifier, then the CPknows that the particular row of anchor points has been completed, andstep 3512 is performed. If the further anchor point does not “run upagainst” a previously identified anchor point, then the CP knows theparticular row of anchor points has not been completed, and the processpasses directly from step 3511 to step 3513A. Either way, a furtheranchor point has been identified that is to be associated with a furtheridentifier. Accordingly, in step 3513A, the proposed anchor point isapproved in the processing to be an “anchor point” upon which boundarieswill be formed about. Then, in step 3513, the CP increments the currentunique area identifier (UAI) so as to generate a new unique areaidentifier. Such increment processing can be performed by adding a levelincrement value on to the current UAI value. Further details aredescribed with reference to FIG. 37 regarding a particular numberingscheme that can be utilized in the processing of the disclosure.Accordingly, step 3513 results in the generation of a new UAI. Then, theprocess passes back to step 3503. In step 3503, the processor indeedassigns that newly determined UAI to represent the current anchor point.Processing then advances to step 3504. Processing then continues asdescribed above. With further reference to FIG. 35, it may be determinedin step 3510, that the processor has determined that the “staking out”of the remote areas has been completed. That is, a yes is rendered instep 3510. As a result, the process passes onto step 3520.

In step 3520, segmentation processing to create the “remote” areas inthe area to be segmented has completed. Thus, the system now has a“remote” area framework to work off of to assign photos in manner asdescribed below. As noted at 3520″, step 3520 reflects that theprocessor has now segmented the current area, which can be the world orpart of the world. The current area can be represented in a databaseusing indicia or attribute to identify the area, which can include datareflecting the level of the particular area.

It should be appreciated that the description herein has been describedin the context of a “remote” area. In this example, such remote area isthe highest level area or largest area that the framework includes. The“remote” area is illustratively 100 miles×100 miles, though suchdistance can be varied as desired. It is appreciated that the term“remote” area could be renamed as desired, and is used herein forpurposes of description. Once the framework has been established,various related processing can be performed. As reflected at 3520′ inFIG. 35, FIG. 36 shows related processing that can utilize the frameworkcreated by the processing of FIG. 35.

As described above, the CP can assign boundaries to each anchor pointthat is represented by a corresponding UAI. Such boundaries can beassigned or demarcated in different manners. In one embodiment, once ananchor point is established for reference to a particular area, thenother points or corner points of the area can also be established.

FIG. 65 is a diagram further illustrating segmentation of an area 6500,in accordance with principles of the disclosed subject matter. Forreference, FIG. 65 includes coordinates 6599. As shown, an area 6550,within the area 6500, has been segmented. The area 6550 is in a row6517. The area 6550 can be identified by an anchor point 6551A. The area6560 can include NW corner point 6552, NE corner point 6553, and SEcorner point 6554. Processing can then be performed to generate a newarea 6560.

In accordance with at least one embodiment of the disclosed subjectmatter, the processor can retrieve the SE corner point 6554, i.e. of thepreviously generated area 6550. The processor can assign coordinates (ofsuch SE corner point of the area 6550) to be the coordinates of proposedanchor point 6561A of the new area 6560. As described above withreference to FIG. 35, such proposed anchor point 6561A can be checked todetermine proximity to other previously created anchor points and/orchecked to determine proximity to a border to the area to be segmented,such as a quadrant of the globe, for example.

If such proposed anchor point 6561A is not proximate in such manner,then such proposed anchor point 6561A is deemed a full fledged orapproved “anchor point”. Accordingly, the processor can advance toassign boundaries to such anchor point.

In the processing to assign boundaries to such anchor point, theprocessor can perform the following.

-   -   Retrieve the anchor point 6561A of the current area 6560 from        memory.    -   The SE corner point 6564 of the new area 6560 can then be        determined by “adding” 100 miles, i.e. the advance value in the        x-direction, on to the anchor point 6561A in the east direction.    -   The NW corner point 6562 of the new area 6560 can then be        determined by “adding” 100 miles, i.e. the advance value in the        y-direction, on to the anchor point 6561A in the North        direction.    -   The NE corner point 6563 of the new area 6560 can then be        determined by “adding” 100 miles on to the NW corner point 6562        in the east direction.

Once segmentation of the row 6517 is completed, the processor canproceed with segmenting the row 6518, i.e. future row 6518.

The segmentation can be described as taking 100 mile square chunks ofarea moving due east along a line, in a row, in accordance with at leastone embodiment of the disclosed subject matter. The processor candetermine that a row, e.g. row 6516, has been completed based on (1)comparison of area to be segmented versus the GPS location of thecurrent proposed anchor point being generated and/or (2) that the GPSlocation of the current anchor point being generated is approaching apreviously generated anchor point. Once segmentation of the row 6516 iscomplete, the processor can advance down to segment a further row 6517,as shown. As shown in FIG. 65, rows 6514 and 6515 have been alreadysegmented.

In alternative processing, the corner point 6562 might be deemed as thenew anchor point 6562, and a new SW corner point 6561A be generatedbased on the newly deemed anchor point 6562. It is appreciated that anycorner point (or a center point) might be used as the reference oranchor point, as may be desired. As shown, segmentation can proceed in adown or south direction. Segmentation could instead proceed up or north,or indeed in any direction as desired.

Accordingly, in this manner, the boundaries, of the area 6560 that isassociated with the anchor point 6561A, can be determined. Also, theanchor point 6561A can be identified or associated with a unique areaidentifier (UAI) as described further below.

Accordingly, each anchor point can be associated with a distinct area.Relatedly, the generation of anchor points, for each respective area,can be performed. In the segmentation processing, the anchor point canbe established in advance of boundaries associated with a given anchorpoint. In the example of FIG. 65, the anchor point 6561A has beenestablished. Once the anchor point 6561A has been established, theboundaries associated with the anchor point 6561A can be established asdescribed above. Then, the processing can determine the next proposedanchor point for the particular row being processed. Such corresponds tothe processing described in step 3505 of FIG. 35. In this example, anext anchor point 6571A can be determined by moving the advance distancein a direction to the east (from anchor point 6561A), as reflected incoordinates 6599.

It is appreciated that the processing that is utilized to demarcateareas of the particular framework can be varied. In the example of FIG.65, remote areas can be carved out in rows progressing in an easterndirection. As one row is completed around the globe or world, then theprocessing drops down (or advances down) to complete the next row. Suchprocessing is reflected in step 3512 of FIG. 35.

However, other approaches and methodologies may be used. For example, anarea can be segmented by going back and forth over the area. Thus, asthe processor identifies that a proposed anchor point has beenestablished proximate to or at a boundary, the direction of segmentationcan be reversed. That is, for example, as segmentation approaches aneastern boundary of the area to be segmented, the processing can bereversed so as to proceed in a western direction. Then, at a point, thesegmentation will reach a western boundary of the area to be segmented.Then segmentation can again be reversed so as to again advance in theeastern direction carving out remote areas, in this example. Suchalternative processing is reflected at 3511′ in FIG. 35. Accordingly,the globe or some other predetermined area can be segmented in whatmight be described as ribbons or layers. As one ribbon or layer iscompleted, i.e. segmented, the processing drops down (or up) to the nextlayer. As a final ribbon or layer is completed in a particular area, theGPS position of the anchor point 6511 can be identified as approachingthe southern or bottom extent of an area to be segmented. Accordingly,akin to step 3510 of FIG. 35, the processor can identify if thesegmentation of the particular area has been completed.

As described above, segmentation can be performed by going around theentire global world in ribbons or layers. Once an anchor point isidentified as being sufficiently proximate a previously created anchorpoint in a row, i.e. a ribbon around the world has been completed, thenthe processing can drop down to “stake out” the next row as reflected instep 3512 of FIG. 35. However, instead, the world could be broken intodiscrete areas and each discrete area segmented separately. For example,the world could be broken into quadrants including a northwest quadrant,a northeast quadrant, a southwest quadrant, and a southeast quadrant.Each demarcated area can be identified by its quadrant. For example, anarea in the northeast quadrant could include the indicia NE in itsunique area identifier. Further details are described below. In oneembodiment of the processing described above, the southeast cornerpoint, i.e. the coordinates of such point, can be used to generate theanchor point 6561A for the next area to be generated, i.e. the area6560, as shown in FIG. 65. Such processing methodology to generate a rowof segmented areas can be utilized even in the situation that there isnot a row above the current row being segmented. That is, themethodology could be utilized even if row 6516 had not previously beengenerated. That is, such methodology can be utilized if there is a rowrunning above the current row being generated, as well as if there isnot a row running above the current row being generated.

However, in some embodiments of segmentation, it can be advantageous torely on an adjacent row, if indeed such adjacent row does indeed exist.For example, coordinates of the southwest corner point of an area 6540,shown in FIG. 65, could be utilized to generate the northwest cornerpoint 6562 for the area 6560. Such interrelationship in forming a newrow based on coordinates of an existing row can decreaseinconsistencies, inaccuracies, and prevent drift. In general, it isappreciated that the generation of a new area in segmentation canutilize any existing area, anchor point, corner point, or otherreference point as may be desired.

As described above, in steps 3510 and 3511 of FIG. 35 for example, aproposed anchor point can be generated. Once the proposed anchor pointis generated, the processor can determine whether that proposed anchorpoint is proximate a boundary of the area to be segmented or whether theproposed anchor point is proximate to another anchor point previouslygenerated to form an area. Such a border or previously generated anchorpoint can be generally described as an “impediment” to the currentproposed anchor point, i.e. in that such impediment impedes the proposedanchor point being deemed an anchor point—and impedes the proposedanchor point being subsequently associated with boundaries and a uniquearea identifier.

To explain further, in generation of remote areas, the advance value inthe X-direction can be 100 miles. For example, the segmentation of a rowcan be approaching the end of the row. As result, a proposed anchorpoint can be, for example, 67 miles from the anchor point of the firstarea in the particular row. In such situation, a fractional or shortened“remote” area can be generated. Such a fractional remote area caninclude the 67 miles that has to still be allocated to a particulararea. Such fractional remote area can still be 100 miles in “height”.Accordingly, the particular row can be fully completed using such a miniarea or fractional area. The segmentation could be engineered such thatsuch a fractional area could be in a remote location unlikely to receivephotos. In addition, a user might be alerted to any such fractional areaby a GUI alert on the user device (UD). Relatedly, in a segmentationmap, such as is shown and rendered in FIG. 37, a fractional area on theright end of a row can complement a fractional area on the left end ofthe same row, so as to collectively form a complete area, such completearea being equal in area to other areas along the length of the row.

Accordingly, various processing to perform segmentation of the world orother geographical area is described above with reference to FIGS. 35and 65.

FIG. 36 a flowchart showing details of “CP associates photo to a patch”of subroutine 3600 as called from FIG. 34, in accordance with principlesof the disclosed subject matter. As reflected at 3600′, the processingof FIG. 36 relies on the segmentation of compartmentalization that wasestablished in the processing described with reference to FIGS. 35 and65. That is, the processing of FIG. 36 relies on the remote areas thatare created in the processing of FIGS. 35 and 65.

The subroutine is initiated in step 3600 and passes onto step 3601. Instep 3601, the CP retrieves the GPS coordinates of the photo. Forexample, the photo may have just been input from a user. Then, theprocess passes onto step 3602. In step 3602, the CP compares the GPScoordinates of the photo against the boundaries of all created patches.Then in step 3603, the CP determines if the GPS coordinates of the photofall within an existing patch. For example, if a previous photo has beenadded into the system from a GPS location proximate the new photo, thenit may well be that a patch will already exist for the new photo.Accordingly, a “yes” may be rendered in the determination of step3603—and the process passed onto step 3604. In step 3604, the CPassociates or places the photo in the identified patch that matched up.The photo has thus found a “home” in a patch that was previouslycreated.

On the other hand, a “no” may be rendered in the determination of step3603. As a result, the process passes onto step 3606. In step 3606, area“fill in” processing is performed. Such processing is performed tocreate a patch into which the photo may be placed. Subroutine 6600 canbe utilized to perform such fill in processing. Details are describedbelow with reference to FIG. 66.

Accordingly, a result of the processing of step 3606 is to create apatch area, i.e. a patch, into which the new photo can be placed. Afterstep 3606 as shown in FIG. 36, the process passes onto step 3607. Instep 3607, the CP proceeds with associating or placing the photo intothe appropriate patch, which was created in step 3606.

As reflected at 3610 in FIG. 36, and in summary, the system can firstcheck to see if a Patch exists for the GPS location of a given photo. Ifso, the Photo is tagged or associated to that unique Patch. If not, thesystem performs processing to create a Patch into which the photobelongs.

The use of established Boundary Markers and/or specific longitude andlatitude points (or GPS location) can be used as part of the creation ofnew Patches, Locals, Quadrants, Sectors, and Territories within theRemote areas. Processing using such interrelationship can serve as partof a reconciliation process and also address rounding issues. It isappreciated that size of areas, names of areas, and number of areas maybe varied as desired. Accordingly, such particulars as described hereinare provided for illustration and are not limiting of the disclosure.

FIG. 66 a flowchart showing details of “area fill-in processing isperformed” of subroutine 6600 as called from FIG. 36, in accordance withprinciples of the disclosed subject matter. The process is initiated instep 6600 and passes to step 6601. In summary, it is appreciated thatthe processing of FIG. 66 is invoked in the situation that a photo isinput into the system and the GPS coordinates of that photo do not matchup within an existing patch area. In such situation, as described below,the processing can include going “up” the segmentation framework untilan area is identified that includes the GPS location of the new photo.Once the area is identified, the processing then “fills in” suchidentified area until a patch is generated that includes the GPSlocation of the new photo. In this manner, the new photo is provided a“home”.

FIG. 66 illustrates such processing. In step 6601, the processor or CPdetermines if a local area exists that includes the GPS location of thephoto. If “yes”, then the processor populates the identified local areawith patches, until a patch is created that includes the GPS location ofthe new photo. That is, in some embodiments, patches will only becreated in the local area until a patch is created that contains the GPSlocation of the new photo. However, in other embodiments, the entirelocal area can be segmented into patches—after which the particularpatch that contains the GPS location of the photo will be identified.Such alternative processing may require additional processing capacityas compared to a situation where patch generation is terminated upon thepatch, containing the GPS location of the photo, being identified. Afterstep 6602, the processing passes onto step 6620.

Relatedly, as reflected at 6602′ in FIG. 66, in some embodiments,processing can be performed that only creates one box, i.e. area, ateach level. Such one box is created so as to contain the GPS location ofthe new photo. To explain further, in the processing of steps 6602,6604, 6606, and 6608, the CP can, at each level, start at a startingpoint and create areas, i.e. boxes, until an area (at the particularlevel) is created that contains the GPS location of the new photo.However, in an other embodiment, only one box can be created at eachlevel. That is, in such other embodiment, only one box, i.e. area, ateach level can be created—with such one area being created to containthe GPS location of the new photo. The one box, in each area, can becreated.

For example, the processing to create an area within a higher levelarea, e.g. a patch within a local, can include the following. If aphoto, having a photo GPS position, is determined to be in a local area,but no patch has been created that contains the photo within itsboundaries, a new patch can be created. The processor (i.e. the CP) candetermine the local, i.e. the local area, in which the new photo isdisposed. The processor can then demarcate out divisions within thelocal area. For example, the local area can be broken into 10 divisionsin the x direction and 10 divisions in the y direction. Each divisioncan be identified with a marker. The processor can identify which twox-markers the photo GPS position is between in the x-direction, as wellas which two y-markers the photo GPS position is between in they-direction. Accordingly, the CP can then create a patch area based onwhich four (4) markers are identified, i.e. which two x-markers boundthe photo GPS position, and which two y-markers bound the photo GPSposition.

The highest value x-marker and the highest value y-marker can define anortheast corner of the patch. The lowest value x-marker and the lowestvalue y-marker can define a southwest corner of the patch. If any of themarkers and/or the corners of the patch are proximate a previouslycreated marker and/or corner—then the previously created marker and/orcorner can be used, so as to provide consistency and smooth continuityof segmentation. This described processing can be applied to otherlevels of areas, as desired.

With further reference to FIG. 66, on the other hand, it may bedetermined in step 6601 that a local area does not exist that includesthe GPS location of the photo. Accordingly, the process passes to step6603. In step 6603, the processor determines if a quadrant area existsthat includes the GPS location of the photo. Accordingly, the processorwill go to higher-level and larger areas to determine an area thatcontains the GPS location of the new photo. If a “yes” is rendered instep 6603, then the process passes onto step 6604. In step 6604, theprocessor populates the identified quadrant area with local areas andpatches, until a patch is created that includes the GPS location of thenew photo. Once a matching patch is created and identified, then theprocessing of step 6604 is terminated. After step 6604, the processpasses onto step 6620. On the other hand, a “no” may be rendered in theprocessing of step 6603. As a result, the process passes onto step 6605.

In step 6605, the processor determines if a sector area exists thatincludes the GPS location of the photo. If “yes,” then processing passesonto step 6606. In step 6606, the CP populates the identified sectorarea with quadrant areas, local areas and patches, until a patch iscreated that includes the GPS location of the new photo. Then, theprocess passes onto step 6620. On the other hand, a “no” may be renderedin step 6605. Thus, the process passes onto step 6600.

In step 6600, the processor determines if a territory area exists thatincludes the GPS location of the new photo. If “yes,” then the processpasses onto step 6608. In step 6608, the CP populates the identifiedterritory area with sector areas, quadrant areas, local areas andpatches. Such processing is performed until a patch is created thatincludes the GPS location of the new photo. On the other hand, a “no”may be rendered in the processing of step 6600. As a result, the processpasses onto step 6610.

In step 6610, the processor determines the remote area that includes theGPS location of the photo. Step 6610 reflects that all remote areas havepreviously been created, in this embodiment of the disclosure.Accordingly, the particular remote area that contains the GPS location,of the new photo, can be determined in step 6610. Then, in step 6611,the processor populates the identified remote area with the territoryareas, sector areas, quadrant areas, local areas, and patches. Suchprocessing to populate the identified remote area is performed until apatch is identified that includes the GPS location of the new photo.That is, processing is performed until a patch is identified as a “home”to the new photo. After step 6611, the process passes onto step 6620.

In step 6620, the processing returns to FIG. 36 with a patch having beencreated that includes the GPS location of the new photo. As describedabove, in step 3607 of FIG. 36, the processor then associates or placesthe photo into the patch that has been created.

It is appreciated that any of the framework generation processing, thesegmentation processing and/or other related processing described hereincan be utilized in conjunction with the processing of FIG. 66. Asdescribed above, in step 6602, 6604, 6606, 6608, and 6611, processingcan be performed until a patch is identified that matches up with theGPS location of the new photo. On the other hand, in another variationof the processing, if a remote area is identified as containing the newphoto, then it might be the case that the entirety of such remote areais populated with territories, sectors, quadrants, locals, and patches.Other selective processing can be utilized so as to identify a matchingpatch as quickly as possible and with minimal processing, if such isdesired. For example, the processing might include determination ofwhere a patch is located in a particular remote area. If a patch islocated adjacent a corner of such remote area, then generation of areaswithin such remote area might be initiated proximate to the identifiedcorner. Other “efficient” processing techniques might be utilized asdesired. As described above, each patch can be identified by a uniquearea identifier (UAI). FIG. 37 is a diagram showing aspects of uniquearea identifier (UAI) generation, in accordance with principles of thedisclosed subject matter. Additionally, FIG. 38 is a further diagramshowing further aspects of UAI generation, in accordance with principlesof the disclosed subject matter.

In accordance with the disclosure, the disclosed methodology canestablish and utilize a unique numbering system. The unique numberingsystem can include the use of unique area identifiers (UAIs). Each UAIcan include a sequence of characters. The sequence of characters can bealpha characters, numerical characters, and/or any other character asmay be desired. In the example of FIG. 37, an illustrative UAI 3701 isprovided. For purposes of illustration, the UAI 3701 includes a sequenceof numbers. Predetermined numbers in the sequence represent a respectivearea.

To explain, the UAI 3701 includes 5 initial numbers or digits. Such 5initial numbers can correspond to a particular remote area, asillustrated in box 3703 of FIG. 37. The next two numbers (in the UAI3701) correspond to a particular territory area. The next two numberscan correspond to a particular sector area. The next two numbers cancorrespond to a particular quadrant area. The next two numbers cancorrespond to a particular local area. And lastly, the final 2 numbersof the UAI 3701 can correspond to a particular patch. Box 3703 in FIG.37 also provides illustrative dimensions for various areas. For example,a territory area can be 10 miles×10 miles. Such dimensions are forpurposes of illustration, and the disclosure is not limited to suchparticulars.

The methodology of the UAI can be powerful in its implementation. TheUAI can identify patches or any other area in an efficient and effectivemanner. Accordingly, use of the UAIs can assist in processing efficiencyand in storage of data in an effective and efficient manner.

In one embodiment of the disclosure, the globe or world can be brokeninto 4 quarters. Segmentation processing can be performed for each ofthe 4 quarters independently. Indicia can be utilized so as to signify aparticular quarter of the globe. Accordingly, each UAI can include twoalpha characters at the beginning of the character sequence for eachUAI, for example. The two alpha characters might include NW for an areain the northwest quarter, NE for an area in the northeast quarter, SWfor an area in the southwest quarter, and SE for an area in thesoutheast quarter. In the situation that an area is broken up intodifferent or additional areas, than other alpha or alphanumericcharacter sequences can be utilized. For example, Times Square in NewYork City might be represented by the UAI:

-   -   NW32111928018078, which corresponds to the latitude and        longitude (Lat-Long) coordinates:    -   40.7599638889,−73.9848416667.

Accordingly, embodiments can include segmentation of the globe (i.e.world) for example into quadrants such as NW; NE; SW; SE quadrants. Theparticular quadrant that an area is located in can be represented asalpha characters. Such alpha characters can be added as a prefix to theUnique Area Identifiers, for example. Such is illustrated above by theabove New York City UAI. Any character sequence can be used to representan area in the form of a UAI.

FIG. 37 also illustrates a further unique area identifier (UAI) 3702.FIG. 37 shows segmented map 3730. The segmented map 3730 includesportions of Mexico, the United States, and Canada. Accordingly, thisexample illustrates that the processing of the disclosure need not be inthe context of the entire globe or world. Rather other smaller areas canbe segmented and the processing limited to such smaller areas, if suchis desired. The map 3730 shows hundreds or thousands of remote areas3731. Each remote area can be represented by a UAI. As shown, the UAI3701 represents a first remote area in Canada. The UAI 3702 represents asecond remote area in Canada, which is adjacent to the first remotearea. The UAI for both remote areas can include a 15 digit number asshown. The first 5 digits of such number can be dedicated toidentification of a remote area. Accordingly, the UAI of the firstremote area 3701 is one (1) digit off of the UAI 3702 that representsthe second remote area. Assignment of a respective UAI to each remotearea is described above with reference to FIG. 35, for example. Inparticular, step 3513 of FIG. 35 relates to incrementing a current UAI(for a current remote area) and incrementing that current UAI by a levelincrement value so as to generate a UAI for the adjacent or next remotearea. FIG. 37 shows level increment value 3720. The level incrementvalue 3720 is crafted so as to increment the appropriate “digits” forthe particular area to which the UAI relates. For example, insegmentation processing, a remote area can be broken into 100territories. Assignment of a UAI to each territory can includeincrementing the appropriate digits of the UA. In the example of FIG.37, such appropriate digits can include the digits 3702′ as shown inFIG. 37. Further, as smaller areas are segmented and UAIs are assigned,the appropriate digits, which represent such smaller area, can beincremented based on the schema shown at 3703 of FIG. 37.

The segmented map 3730 of FIG. 37 shows many remote areas. Each of theremote areas, in this example, is 100 miles×100 miles. The segmented map3730 is graphically expanded at the top so as to render the map shown inFIG. 37 to be square. As a result, the areas 3731 toward the top of themap appear larger than areas at a lower portion of the map. This is aresult of the rendering of the map 3730 so as to be in the rectangulargeometry as shown. Thus, it is appreciated that the areas 3731 at thetop of the map are indeed the same geographical 100 miles×100 miles asthe areas 3731 at the bottom of the map.

As described above, in segmentation of a particular area, ifsegmentation reaches the end of a row and/or attains a boundary of thearea to be segmented, an area can be segmented so as to be smaller, i.e.so as to accommodate the residual area of the particular row that isremaining. Accordingly, this is apparent from the segmented map 3730 inwhich areas on opposing ends of the rows may be of different size thaninternal areas within the rows.

In further explanation of the UAI, FIG. 38 is a diagram that illustratesthe UAI of a local area 3800A, in accordance with principles of thedisclosed subject matter. The UAI is 10700-25-10-01-07 for theparticular local area, in this example. Dash separators can be used soas to better visually decipher a particular UAI. In processing, theprocessor can disregard such dash separators.

As reflected at 3810 in FIG. 38, each UAI can correspond to an area ofspecific coordinates. For example, a patch area—the smallest area—can berepresented by a 15 digit number. A local area can be represented by a13 digit number or in other words the first 13 digits of the UAI.Further, a remote area can be represented by 5 digit number or in otherwords the first 5 digits of the UAI. Further, determination of childareas in a parent area can be determined by searching and comparison ofUAIs. FIG. 38 shows a plurality of patch areas 3801 in a row. Inprocessing, it should be appreciated that UAIs can be utilized andmanipulated in various ways. For example, in the local area shown inFIG. 38, the UAI for each patch in the local area is the same.Accordingly, different UAIs can be compared to determine if they areindeed from the same remote area, territory, sector, quadrant, or localarea. Further, the entire UAI can be transferred in processingcomponents and stored in databases—and portions of the UAI be used asdesired. For example, if it is desired in processing to determine whichpatches are in a particular remote area, then only the first 5 digits ofsearched UAIs might be utilized. Other processing and manipulation ofUAIs may be performed.

The 15 digit UAI, to represent a particular remote area—and areas withinsuch remote area—is for purposes of illustration. As shown, a specificdigit or group of digits in the UAI can correspond to a particular area,as is the case with the UAIs illustrated in FIGS. 37 and 38. Theparticular format of the UAI may be varied as desired.

Hereinafter, further details of the systems and methods of thedisclosure relating to visualization processing will be described. Suchprocessing relates to the effective and efficient display of a varietyof data, including image data, on a user device, for example.Accordingly, FIG. 39 is a flowchart showing “processor processes userrequest for display of “visual area” on user device (cell phone)” ofsubroutine 3900, in accordance with principles of the disclosed subjectmatter. As shown in FIG. 39, the processing is initiated in step 3900.For example, the processing of FIG. 39 might be initiated when a userzooms in on a particular area of interest, so as to view photos in theparticular area of interest. Once initiated, the processing passes ontostep 3901 of FIG. 39. In step 3901, the processor interfaces with theuser to input a visual area to display on the user device. The processorcan be located on a server remote from the user device and incommunication with user device. The processor can be located on the userdevice. The processor can be located partially on the user device andpartially on a remote server. After step 3901, the process passes ontostep 3902. In step 3902, the processor determines or retrieves the GPScoordinates of the 4 corners of the visual display of the user device.The GPS coordinates can be saved in short-term memory or in transientmemory for further processing. Such GPS coordinates can be described asvisual area coordinates. Further, a visual display, on a user device,can be described as a “drawn map”. As reflected at 3902′, the GPScoordinates can be converted into another coordinate system and/or othercoordinate systems can be utilized in the processing of the invention.For example, a longitude and latitude coordinate system; x and ycoordinate system, or other coordinate system can be utilized in thesystems of the disclosure. In some embodiments, two opposing corners(e.g. southwest corner and north east corner coordinates) can be inputand the visual display or area of display be determined based on suchcoordinates.

After step 3902, the process passes onto step 3903. In step 3903, theprocess determines the level that the visual display is currentlydisplaying. Subroutine 4000 as shown in FIG. 40 can be invoked. Then,the process passes onto step 3904. In step 3904, the processor, based onvisual area (VA) coordinates, determines a search bound area. Suchsearch bound area can be represented in coordinates. Subroutine 4100 asshown in FIG. 41 can be invoked for such processing.

After step 3904, the process passes onto step 3905. In step 3905, theprocessor performs pin placement processing for the current visual area(VA) that is being displayed on the user device. Such processing can beperformed for the particular zoom level that is being displayed on theuser device. Depending on the particular zoom level being displayed onthe user device, details of different levels can be displayed. Forpurposes of illustration, it is assumed in step 3905 that the particularzoom level being displayed on the user device is the “local” level, i.e.meaning that a plurality of local areas are displayed on the userdevice, in this example. If a plurality of sector levels are displayedon the user device, such might be described as—the particular zoom levelbeing displayed is the “sector level”. However, for this particularexample, the local level is being displayed. As a result, subroutine4200 of FIG. 42 can be called upon or invoked. Accordingly, subroutine4200 is illustrative of pin processing at the local level. However, asreflected at 3905′ similar respective processing can be performed if itis determined that another level is being displayed on the user device,i.e. as a result of the particular zoom setting on the user device.

FIG. 40 is a flowchart showing “processor determines the level that thevisual area (VA) is currently displaying” of subroutine 4000, as calledfrom the processing of FIG. 39, in accordance with principles of thedisclosed subject matter. As shown, the subroutine is launched in step4000 and passes onto step 4001. In step 4001, the processor determinesthe “zoom level”, or more generally the level of resolution, that theviewport area is currently displaying. It is appreciated that theillustrated zoom levels are for purposes of illustration. The zoom levelcan be input from the user device as a zoom level or number. The zoomlevel can be input from the user device as a percentage value, forexample. Depending on the particular zoom level identified, theprocessor can determine which level is to be displayed on the userdevice and can determine other attributes of the processing to beperformed. For example, if the zoom level is between 6 and 7, theprocess passes onto step 4011. In step 4011, the processor tags thecurrent level as being at the patch level.

If the zoom level is between 5 and 6, the process passes onto step 4012.In step 4012, the processor tags the current level as being at the locallevel. As noted above, processing at the local level is illustrativelyshown in subroutine 4200 described below with reference to FIG. 42. Ifthe zoom level is between 4 and 5, the process passes onto step 4013. Instep 4013, the processor tags the current level as being at the quadrantlevel.

If the zoom level is between 3 and 4, then the process passes onto step4014. In step 4014, the processor tags the current level as being thesector level. If the zoom level is between 2 and 3, then the processpasses onto step 4015. In step 4015, the processor tags the currentlevel as the territory level. Further, if the zoom level is between 1and 2, then the process passes onto step 4016. In step 4016, theprocessor tags the current level as the remote level. As shown in FIG.40, after identifying the particular level (that processing is occurringat) in one of steps 4011, 4012, 4013, 4014, 4015, 4016—the process thenpasses onto step 4020. In step 4020, the process returns to FIG. 39.Specifically, the process passes onto step 3904 with the identifiedlevel in transient memory, for later processing.

FIG. 41 is a flowchart showing “processor, based on the coordinates ofthe Viewport Area (VA), determines search bound coordinates” ofsubroutine 4100 as called from the processing of FIG. 39, in accordancewith principles of the disclosed subject matter. As shown, thesubroutine is initiated in step 4100 and passes onto step 4101. In step4101, the processor retrieves the zoom level from transient memory, assuch zoom level was determined in the processing of FIG. 40. After step4101, the process passes onto step 4102. In step 4102, the processretrieves coordinates of the area being viewed on the user device. Forexample, coordinates retrieved can be the southwest corner coordinatesof the viewport area and the northeast corner coordinates of theviewport area. Such corner coordinates can convey the particularviewport area being displayed on the user device. Other coordinatesand/or attributes of the displayed image can be used to determine thearea being viewed on the user device.

Then, the process passes onto step 4103. In step 4103, the processorapplies an expansion factor to the viewport area. The expansion factoris applied to generate a buffer or “search bounds (SB)” around theviewport area. In other words, the expansion factor might be describedas determining an area that is added to each corner of the viewportarea. The expansion factor might be described as determining an areathat is added around the edge of the viewport area, so as to frame theviewport area. Such processing effectively adds a band, i.e. the searchbounds, around the viewport area. As described below, “pins” and/orphotos that are identified in the search bounds can affect display ofdata in the viewport area. For example, the expansion factor could be0.4 or 40% of the viewport area.

After step 4103, the process passes onto step 4104. In step 4104, theprocessing passes onto step 3904 (FIG. 39) with the coordinates of thesearch bound area in transient memory.

FIG. 42 is a flowchart showing “processor performs pin placementprocessing for the current viewport area that is being displayed on theuser device” of subroutine 4200 as called from the processing of FIG.39. As described above, the processing of FIG. 42 is set forth in thecontext of “local” level processing. However, it is appreciated thatsimilar processing can be applied to other levels as may be desired. Asshown in FIG. 42, the subroutine 4200 is launched in step 4200 andpasses onto step 4201. In step 4201, the processor determines all thelocal areas that have a center point within the search area, i.e.,within the search bounds (SB) as determined in the processing of FIG.41. These local areas, which are identified as having a center pointwithin the search area, are saved into transient memory for furtherprocessing. Such local areas can be described as “identified areas” andcan be identified by their respective UAI and boundaries. As reflectedat 4201′ in FIG. 42, processing illustrated in FIGS. 42-44 is describedin the context of processing in the “local” level. However, it should benoted that similar processing can be performed at any level, as desired.The particular level at which processing is performed can depend on theparticular zoom level at which the user is viewing a segmented map, forexample.

After step 4201, the process passes onto step 4202. In step 4202, theprocessor performs “pin placement processing” for each area identifiedin step 4201. To perform such processing, subroutine 4300 can be calledupon or invoked. Such subroutine 4300 is described below with referenceto FIG. 43. In the processing of step 4202, (and as reflected at 4202′)the processor can determine where to put or place a pin on the userdevice. In accordance with some embodiments, each pin can represent atleast one photo.

In some embodiments, in particular in areas more densely populated withphotos, a pin might only be generated if a threshold number of photosare in a particular area. For example, a local area might only display apin if 10 photos are in the particular local area.

In some embodiments, each pin, so as to be viewed, may be required tofall within the viewport area. In other words, the pin may be requiredto fall within the viewport area so as to be seen on the user device.Placement of the pin on the user device can be based on pin densityand/or photo density in lower levels. Accordingly, placement of a pin ata given level can be based on density of photos at one level below suchgiven level. Placement of a pin at a given level can be based on densityof photos at multiple levels below such given level. Thus, for example,placement of a pin (in the situation that the local level is beingdisplayed) may depend on density of photos at the patch level. In otherwords, in some embodiments, processing can use photo density at morethan one level down from the current level being viewed, so as toaccurately position a pin(s) at the current level. Each pin can includea displayed number so as to convey the number of photos that theparticular pin represents. Further details are described below.

After step 4202, the process passes onto step 4206. In step 4206, thegenerated display is displayed on the user device, and the processingroutine is stopped.

FIG. 43 is a flowchart showing “processor performs pin placementprocessing for area” of subroutine 4300, as called upon from theprocessing of FIG. 42, in accordance with principles of the disclosedsubject matter. The process of FIG. 43 is directed to pin placementprocessing at the “local” level, for purposes of illustration.Relatedly, FIG. 44 is a schematic diagram also showing features of pinplacement processing, in accordance with principles of the disclosedsubject matter.

The subroutine 4300 is launched in step 4300 and passes onto step 4301.In step 4301, the processor designates the first local area forprocessing. For example, the local area 4411, shown in the illustrativedisplay of FIG. 44, might be designated as the first area forprocessing. Then, the process passes onto step 4310.

In step 4310, the process retrieves a photo count of all patches, i.e.the next level down, from the “local” area that is being processed.Then, the process passes onto step 4311. In step 4311, the processordetermines the patch with the highest photo count. To explain furtherwith reference to tag 4311′, in this processing, the processor usesdensity of photos in child areas (here patches) to position pins inareas being displayed (here local areas). Accordingly, a placed pinlocation can be based upon density of photos in a lower level area oreven multiple lower level areas, e.g. two levels down from the currentlevel. Note, as described below, pin placement can be adjusted if thepin would otherwise be placed out of the viewport area. In other words,as reflected at 4311, pin location in a level can be based on a dominantchild, of a given level.

After step 4311, the process passes onto step 4312. In step 4312, adetermination is made of whether the patch with the highest photo countdoes indeed have a center point that is in the viewport area.Accordingly, at this point in the processing, the patch (having highestdensity of photos) that will dictate pin placement has been determined.However, it is still to be determined whether such patch has a centerpoint in the viewport area. If the center point is not in the viewportarea, then adjustment is needed, else the pin will not be visible to theuser. Accordingly, if a “yes” is rendered in the determination of step4312, then the process passes onto step 4314.

In step 4314, for the local area in the viewport area, the processordisplays the pin at the center point of the highest density child, herea patch. On the other hand, a “no” may be rendered in step 4312. If a“no” is rendered in step 4312, the process passes to step 4313. In step4313, the processor shifts the pin for the local area so that the pin isindeed displayed in the viewport area, otherwise the user would not seethe pin on the user device. In other words, such processing can bedescribed as identifying that, without adjustment, the pin would bedisplayed in a sliver that is outside of the viewport area of the userdevice. Accordingly, adjustment is made such that position of the pin ismoved inside or just inside the viewport area. This processing, ofadjustment of pin placement, occurs with areas 4411 and 4414, shown inFIG. 44 After either of steps 4313, 4314, the process passes onto step4320. In step 4320, the process determines whether there are additionallocal areas to process. For example, in the viewport area 4401 of FIG.44, there are four local areas to process. If “yes” in step 4320, theprocess passes to step 4321. In step 4321, the processor designates thefurther local area for processing. Then, the process passes onto step4310. Processing then proceeds as described above. On the other hand, ifa “no” is rendered in step 4320, the process passes onto step 4330. Instep 4330, the process returns to FIG. 42. Specifically, the processpasses to step 4206 of FIG. 42.

As described above, FIG. 44 is a diagram showing features of pinplacement processing, in accordance with principles of the disclosedsubject matter. FIG. 44 provides a schematic diagram 4440 illustrating acomputer perspective of data 4440.

As reflected at 4420 in FIG. 44, pin positions of a displayed area canbe based on child density. In other words, pin positions of a displayedarea can be based on density of photos in child areas, of the area beingdisplayed. As shown in FIG. 44, the diagram shows a viewport area 4401.The viewport area 4401 includes a plurality of local areas, in whichphotos have been identified. The local areas include areas 4411, 4412,4413, and 4414. FIG. 44 also shows a search bounds 4402. With referenceto the viewport area 4401, the point A represents the location (in localarea A) of the patch, of local area A, having the highest density ofphotos. The point B represents the location (in local area B) of thepatch, of local area B, having the highest density of photos. The pointC represents the location (in local area C) of the patch, of local areaC, having the highest density of photos. The point D represents thelocation (in local area D) of the patch, of local area D, having thehighest density of photos. Accordingly, the viewport area 4401illustrates a computer perspective of data.

FIG. 44 also shows representation of a GUI 4450. As reflected at 4450′,the dashed objects in the GUI 4450 would not be seen by the user in theGUI, but are shown in FIG. 44 for illustration from the perspective ofprocessing. The GUI 4450 shows a pin 4412P. The location of the pin4412P is based on, in this embodiment, the patch having highest densityof photos in the local area B. However, such pin 4412P can reflect thecount of all photos in the local area B. Thus, to reiterate, while thelocation of the pin 4412P can be based on the patch with the highestdensity of photos, the count of the pin 4412P indeed reflects all thephotos in the particular local area. Similarly, the pin 4413P reflectslocation of the patch having highest density in the local area C andalso reflects the total count of photos in local area C.

The GUI 4450 also shows pin 4411P and pin 4414P. However, the positionof such pins in the GUI 4450 have been altered or adjusted vis-à-visposition of the points A and D, respectively, in the search bounds 4402,i.e. as shown in the upper diagram 4440 of FIG. 44. That is, theprocessing adjusts the location of the pins 4411P, 4414P since such pinswould not otherwise be viewable in the viewport area 4401′. Accordingly,the processing of the disclosure can adjust the position of pins thatare identified in a search bounds 4402. The position of such pins can beadjusted so as to be just inside the viewport area 4401′. That is, inthe processing of the disclosure, a pin can be placed as close aspossible to the highest density, in terms of photos, of a child area,yet still be in a viewport area 4401′. Even though a pin may be adjustedin position, such pin can still reflect the total number of photos inthe patch, or other area, that the pin represents. As shown, all thepins have been adjusted to not be present in the search bounds 4402′,which surrounds the viewport area 4401′. As otherwise noted herein, theprocessing of FIGS. 43 and 44 could be applied to areas of other levels,as desired.

FIG. 45 is a schematic diagram showing further aspects of pinprocessing, in accordance with principles of the disclosed subjectmatter. The diagram shows a GUI display 4501 and GUI display 4502. Asreflected at 4500′, a pin 4611 is shown on the left, in GUI display4501, with 42 photos. Other pins can also be displayed in the GUIdisplay 4501. The particular pin 4611 represents the number of photos inarea 4510. A user can zoom in on the pin 4611. When a user “zooms” in onthe pin 4611, the GUI display 4502 is generated, i.e. the display on theright is generated. That is, the GUI display 4502 shows the area 4510expanded or “zoomed in on”. In the display 4502, the pin 4611 is seen torepresent photos of a plurality of child areas 4520. The total sum ofphotos of the child areas are represented in the pin 4611. There are 42photos represented by the pin 4611. This count of photos can be seen bythe plurality of pins in the GUI display 4502. Accordingly, the diagramof FIG. 45 demonstrates that count shown, in a pin 4611, can reflect anaggregation or accumulation of pins in lower areas, e.g. pins 4520included in lower areas of the area 4510. Relatedly, as a user “zooms”OUT of an area, the count of photos as represented by a pin, i.e. pincount, may increase since an area represented by such pin can increase,so as to accumulate or aggregate more photos to the particular pin.Inversely, as a user zooms IN, pin count (as represented by a particularpin) may go down. Relatedly, a pin might only be shown in a particulararea if the photo density, in such area, satisfies a predeterminedthreshold.

FIG. 46 is a schematic diagram showing further aspects of pinprocessing, in accordance with principles of the disclosed subjectmatter. In particular, FIG. 46 illustrates pin placement in an areabased upon density of photos in a lower level area. Accordingly, FIG. 46is provided to supplement other related disclosure herein. On the righthand side of FIG. 46, in the GUI 4630, the pin placement for area 4600(with 58 pins) is not the center point of the area 4600, as reflected at4600′. Rather, in light of the left hand side of FIG. 46 and theaccumulated photos totaling 58, the pin placement for the area 4600 (inGUI 4630) can be based on the lower level pin with the highest density,i.e. the pin 4601 that represents 25 photos. That is, pin placementpoint in the area 4600, in the GUI 4630, can be based on the highestdensity child pin position (pin 4601), versus being in the center of thearea 4600. Accordingly, as reflected at 4600″, position of a highestdensity child can alter pin position in a parent area. That is, pinposition in the parent can be altered from being in the center of thearea. Accordingly, pin placement at a particular “zoom” level, displayedon a user device, can be based on density of pins one level down fromthe particular level being displayed. In some embodiments, pin placementcan be based on one, two, or more levels down from the level that isbeing displayed. An advantage of basing pin placement on pin densityand/or photo density at a lower level (than is being displayed) is toposition pins more in line with actual position of photos that aredriving the particular pin. Alternatively, a pin displayed in aparticular area such as a “local” area (to represent the count of photosin the area) could be displayed at some default position. For example,the pin could be displayed at the center of a particular area. However,such default position of a pin may be mis-leading as to where in sucharea the photos are indeed concentrated. Further, it is appreciated thatpin placement in an area at the lowest level, for example a “patch”area, can be based on photos at that lowest level, i.e. since there isno lower level.

Relatedly, a pin might only be generated in a particular area if photodensity in the particular area exceeds a predetermined threshold, forexample, if photos in the area exceed 10 photos. However, in someembodiments, a pin might be generated based on only one photo in aparticular area.

FIG. 47 is a schematic diagram showing yet further aspects of pinprocessing in conjunction with manipulation of thumbnails, in accordancewith principles of the disclosed subject matter. FIG. 47 showsprocessing relating to a GUI 4700. The GUI 4700 is transformed from an“initial state” to an “image selected state” as shown in window 4710 andwindow 4720, respectively. The GUI 4700 can include pin 4711. Other pinscan be displayed as shown in the GUI 4700. The GUI 4700 can also includea plurality of images 4701 provided in a bottom portion or window of theGUI 4700. The images 4701 can include or be in the form of thumbnailphotos. The images 4701 can include image 4702. The user can select theimage 4702 from the scrolling set of images in the window 4710. As aresult, the display shown in window 4720 is generated. The image 4702can be dynamically linked to the pin 4711. When the user clicks theimage 4702, the pin 4711 can become enlarged, change color, or in someother manner be distinguished from the other pins. As shown, a pop-upinformation window can be provided in the window 4720. Such informationwindow can relate to the pin 4711 and the corresponding selected image4702.

Relatedly, various features provided by the systems and methods of theinvention are illustrated in note box 4701N. Scrolling thumbnails orimages 4701 at the bottom of the GUI 4700 can be dynamically linked topins in the windows 4710, 4720. Once a user clicks a pin 4711 in thewindow 4710, at least one image can be shown that corresponds to suchclicked pin. For example, the most popular images can be shown thatcorrespond to the pin that was clicked. A user can toggle between pin tothumbnail. A user can toggle between thumbnail to pin. Color change,change in size, or other distinguishing characteristic can be used todistinguish a selected image 4701 or pin 4711. Accordingly, as reflectedat 4700N of FIG. 47, a popup InfoWindow with data related to a pin andselected image can be generated upon clicking an image 4702—and the pinrelated to the selected image 4702 can become enlarged and highlighted.Accordingly, thumbnails at the bottom of a generated GUI can beassociated with pins represented on the screen of the GUI. Thumbnailscan be arranged by algorithm at the bottom of the screen. For example,thumbnails can be ranked based on a number of associated photos that areassociated with the particular thumbnail. A user can be provided theability to scroll through thumbnails ranked in order of pins in thewindow 4710. Touch of a thumbnail can highlight the pin so as todifferentiate the particular pin. Touch of a thumbnail can toggle to arelated pin location in the window 4710. Additionally, a user can touchpin display ranked thumbnails related to the pin. Thumbnails can bepresented in a variety of orders, starting with the most popularthumbnail. The ability to toggle from thumbnail to spot, for example,can be provided. That is, a spot can be a patch area that has attained apredetermined threshold of photos contained in such patch. The abilityto toggle from spot to detailed information, about the spot, can beprovided. It is appreciated that the functionality described withreference to FIG. 47 can similarly be applied to a level as desired.That is, the system of the disclosure can provide similar functionalityfor any of the levels described herein, as desired.

Hereinafter, further features of the disclosure will be described thatrelate to censorship processing. FIG. 48 is a flowchart showing detailsof a processor of the disclosure performing censorship processing, inaccordance with principles of the disclosed subject matter. Thecensorship processing can relate to a nominating process to “flag” aphoto for various reasons. The processing is not limited to photos. Thatis, the censorship processing can be applied to comments or other mediaor content, including a video, sound media, and/or text content, forexample. As shown, the process starts in step 4800 and passes onto step4801.

In step 4801, the processor presents a photo to the user. For example,such presentation of a photo may be performed via a display on a userdevice, such as a cell phone shown in FIG. 52. FIG. 52 is a schematicdiagram of a user device with GUI, in accordance with principles of thedisclosed subject matter. After step 4801, in step 4802, the processorinterfaces with the user to input selection of a flag selector. The flagselector may be in the form of a button 5212 of a GUI 5210 on a userdevice 5200. A photo 5211 can be displayed on the GUI 5210. The user canidentify some deficiency or concern with the photo 5211. Accordingly,the user can tap the flag button 5212, so as to flag, in some manner,the photo 5211. It is appreciated that the particular photo, about whichthe user wishes to flag, could be identified in some other manner thatis different from the visual selection shown in FIG. 52.

With further reference to FIG. 48, after step 4802, the process passesonto step 4803. In step 4803, in response to selection of the flagselector button, the processor presents flag options to the user. Suchflag options reflect different possible treatment of the particularphoto that was selected. Such flag options can be presented utilizing aflag selector or menu 5213 as shown in FIG. 48 and FIG. 52, and noted at4800′ in FIG. 48. As shown in the menu 5213, options can be providedincluding correct photo, revise photo, remove photo, and tag photo, forexample. It should be appreciated that various other options might alsobe provided regarding possible treatment of the photo. The flag optionsmay include additional information as to the rationale for suchtreatment. For example, the user may flag to “remove photo” and providethe reason. For example, the reason may include violent content,pornography or bullying, as shown in a related menu 5214. The flagselector or menu, with further delineation in a series of subsequentflag selector rationale or menu(s) can be provided in the form ofrespective pop-up menus 5213 and 5214, as shown in FIG. 52.Alternatively, such tagging can be input from the user in some othermanner. As reflected in FIG. 48, some flag options, such as correctionor removal for example, can be associated with text. For example, if auser, i.e. a nominator, is flagging a particular photo forcorrection—such user might also provide comment/text regarding basis forcorrection. Accordingly, a “flag” can be selected from the “flag” pop-upmenu 5213—and once a particular flag is selected, a corresponding“reason” pop-up menu 5214 can be generated. The user can then select areason from the “reason” pop-up menu 5214. The user might also be ableto “type in” their own flag and/or reason. The functionality can providefurther depth of understanding as to why a user objects to a particularphoto or other media.

After step 4803, the process passes onto step 4804. In step 4804, theprocessor inputs the selection, of the flag option, from the user. Theflag option can be associated with a desired action. For example, theflag option “remove photo” can be associated with the action of removingthe photo from one or more collection of photos in the system. Forexample, the photo might be removed from public access. The user whoflags the photo can be described as a “nominator” for the photo. Asdescribed below, the nominator can be associated with particularattributes. Attributes of a nominator can vary depending on theparticular flag type. For example, a nominator may be “stronger” withrespect to one flag type as opposed to another flag type. After step4804, the process passes onto step 4805. In step 4805, the processorperforms ratification processing. Such ratification processing can beperformed by subroutine 4900 of FIG. 49.

Accordingly, FIG. 49 is a flowchart showing “processor performsratification processing” of subroutine 4900, in accordance withprinciples of the disclosed subject matter. Such subroutine can becalled from the processing of FIG. 48. The subroutine is launched instep 4900 and passes onto step 4901.

In step 4901, the processor retrieves a censorship power rating (CPR) ofthe user, who is a nominator, from the user profile. The censorshippower rating can be based on the particular flag that was selected. Thatis, power ratings can vary, for a particular user, based on what flag isselected. A particular flag can include sub flags or other underlyingdelineation. Also, channels can be provided and a particular flag (orsub-flag) can be allocated to a particular channel. The flag, sub flag,underlying delineation and/or established “channels” can be based upon“location types” as shown in FIG. 12 step 613, for example. A user mightbe very weak with regard to one type of flag (or sub-flag), and verystrong with regard to another type of flag (or sub-flag). Suchvariation(s) in strength of a user may also be provided whereby a useris weak in one flag type in a given “channel” and very strong in thesame flag type in another “channel”. Also, different user bases can beprovided. Each user base can be associated with, i.e. include, aparticular group of users. A user base for a given “channel” may havediffering norms or settings for censorship, as compared to a user basefor another channel. Accordingly, the censorship power rating (CPR) ofthe user (and other parameters that are used in censorship processingand related processing), can be dictated by a variety of attributesincluding flag associated with a photo, sub-flag associated with aphoto, underlying delineation associated with the photo, channel inwhich a flag is disposed, channel in which the photo is disposed, userbase to which the user is associated, and other attributes.

With further reference to FIG. 49, after step 4901, the process passesonto step 4902. In step 4902, the processor maps the CPR of the user tothe required ratification number (RRN) for the requested action. Suchmapping can be performed utilizing the processing of FIG. 51. Then, theprocess passes onto step 4903. In step 4903, the processor retrieves theaccumulated ratification number (ARN) that has built up for therequested action, for the particular photo. If ratification processinghas just begun for the particular photo, the accumulated ratificationnumber may be 0. Then, the process passes onto step 4904. In step 4904,the processor determines whether the number of persons who haveratified, as represented in the accumulated ratification number, satisfythe required ratification number. That is, has the threshold for thepredetermined action been attained or not attained. If a “yes” isrendered in step 4904, the process passes onto step 4906.

In step 4906, the censorship power rating (CPR) of the user isincremented (for a positive ratification) in some manner. In thisexample, the CPR is incremented by the value of 1. However, it isappreciated that other methodologies can be utilized so as to increasethe CPR of the user. Accordingly, as reflected at 4906′ of FIG. 49, theCPR of the nominator, i.e. the user who nominated the flag, can beincreased for a positive ratification. As a result, the next time thatthe nominator nominates a photo, for a particular flag, fewer ratifiersmay be needed. This is because the nominator's strength, as to theparticular flag, has increased as reflected in his or her CPR.Relatedly, as reflected at 4900′ in FIG. 49, for a new user, forexample, the new user may have a higher required ratification number(RRN), as compared with an older user with a strong CPR, and thus ahigher accumulated ratification number (ARN) may be required in order toperform the particular action requested by a selected flag. After step4904, the process passes onto step 4907. In step 4907, the processorperforms the action that has been selected by the user. That is, theprocessor performs the action that is associated with the flag selectedby the nominator user.

On the other hand, a “no” may be rendered in the processing of step4904. Such a no indicates that a sufficient number of ratifiers has notbeen attained so as to perform the action requested by the nominator.

Accordingly, the process passes onto step 4904N in FIG. 49. In step4904N, the processor determines: does the number of persons who havenegated (i.e. disagreed with) the nominator (as represented by ARN)satisfy a lower threshold? If “yes”, then the process passes onto step4906N.

In step 4906N, the censorship power rating (CPR) of the user isdecremented (for a negative ratification) in some manner. In thisexample, the CPR is decremented by the value of 1. However, it isappreciated that other methodologies can be utilized so as to decreasethe CPR of the user. Accordingly, the CPR of the nominator, i.e. theuser who nominated the flag, can be decreased for a negativeratification. As a result, the next time that the nominator nominates aphoto, for a particular flag, MORE ratifiers may be needed. This isbecause the nominator's strength, as to the particular flag, hasdecreased as reflected in his or her CPR.

Then, in step 4907N, the processor removes the flag. That is, thenominator has been overruled.

As noted herein, other methodologies can be utilized so as to increaseor decrease the CPR of the user, such as in steps 4906, 4906N, 5004(FIG. 50) and/or 5005 (FIG. 50). Such other methodologies can includeother additive processing, multiplicative processing, use of thresholds,and/or use of absolute values. For example, step 4904 can includedetermining if the accumulated ratification reaches an absolute value of“X” and/or a multiplicative value of “Y”. For example, step 4904N caninclude determining if the accumulated ratification reaches an absolutevalue of “X” and/or a multiplicative value of “Y”.

On the other hand, if no in step 4904N of FIG. 49, the process passesonto step 4905 of FIG. 49. In step 4905, the CP or processor performsaccumulated ratification processing. Subroutine 5000 of FIG. 50 can becalled upon to perform such processing. In such ratification processing,as reflected at 4905′, the processor waits for further ratification fromother users and/or waits for further disagreement from other users. Onceratification processing has been performed in step 4905, the processloops back to step 4903. Processing then continues as described above.

Accordingly, FIG. 50 is a flowchart showing “processor performsaccumulated ratification processing” of subroutine 5000 as invoked fromFIG. 49, in accordance with principles of the disclosed subject matter.The subroutine is launched in step 5000 and passes to step 5001. In step5001, the processor waits for other users to interface with the systemwith regard to the particular photo and particular flag. As reflected at5000′, a nominator can be constituted by a first user device, andratifiers can be constituted by additional respective user devices.

Once a user interfaces with the system, a “yes” is rendered in thedetermination of step 5001. Thus, the process passes onto step 5002. Instep 5002 using a suitable GUI window, the processor interfaces with theuser (a ratifier) to present action, on the photo, that has beenrequested by the nominator. Relatedly, as reflected at tag 5002′, acheck can be performed by the processor to confirm that the other user,i.e. a potential ratifier, has not already ratified this photo for thisparticular flag. After step 5002, the process passes onto step 5003. Instep 5003, the processor determines whether or not the ratifier didindeed agree with the nominator.

If the determination of step 5003 renders a “yes,” then such “yes”constitutes a ratification by a ratifier, as reflected at 5005′ in FIG.50. The process then passes to step 5005. Step 5005 reflects processingfunctionality that action by the ratifier may be magnified. That is,some ratifiers may carry more weight than other ratifiers. In theexample of step 5005, if the ratifier is a superuser, then the ARN gets2 points. If the ratifier is not a superuser, then the ARN gets only onepoint. It is appreciated that other methodologies can be utilized so asto magnify the decision of a favored ratifier. For example, othersummation techniques could be utilized and/or other multiplicationtechniques could be utilized so as to magnify the decision of a favoredratifier, in a magnitude and manner as desired. In the processing ofstep 5005, such processing may or may not be based on flag type. Thatis, the CPR of the user might only be increased for that particular typeof flag. After step 5005, the process passes onto step 5006.

On the other hand, a “no” may be rendered in the determination of step5003. As reflected at 5004′ of FIG. 50, a “no” constitutes a negation bya ratifier. That is, such negation will count against the actionrequested by the nominator. Note, even though the decision or “vote” isagainst the nominator, the particular user or user device is stillconsidered a ratifier for purposes of description herein. Accordingly, a“ratifier” can either agree with a nominator with respect to a flaggedphoto or disagree with the nominator with respect to a flagged to photo.

The processing then passes onto step 5004. Similar to step 5005, but inreverse, step 5004 is provided to magnify the negation of some users.That is, if the ratifier is a superuser, then the ARN is decrementedminus 2 points. Otherwise, the ARN is decremented minus 1 point. Othermathematical processing can be used so as to decrement the ARN. In theprocessing of step 5004, such processing may or may not be based on flagtype. That is, the CPR of the user might only be decreased for thatparticular type of flag. Thus, the process can include censoring thecensurer, i.e. censoring the nominator user. In some embodiments, auser's privilege to flag a photo can be disabled. For example, if athreshold number of flags, which were flagged by a particular nominatinguser, are not ratified—then the user's ability to flag a photo might bedisabled. Such disablement might apply to that particular flag. Further,a user might be disabled in general, i.e. the user is not allowed (bythe system) to flag a photo with any flags.

After step 5004 of FIG. 50, the processing passes onto step 5006. Instep 5006, the processor saves the updated ARN that has built up for therequested action, for the particular photo. Then, the process passesonto step 5007. In step 5007, the process returns to FIG. 49—and inparticular to step 4903 of FIG. 49. Processing then continues asdescribed above.

FIG. 51 is a diagram showing aspects of censorship power rating (CPR)and required ratification number (RRN), in accordance with principles ofthe disclosed subject matter. FIG. 51 shows table 5100. The table 5100includes a plurality of data records 5101. The data records 5101 includevarious data that can be used in censorship processing.

As reflected at 5121, the CPR of a nominator can be mapped to aparticular RRN. The RRN can correlate to how strong the nominator is. Alow RRN can mean that fewer or no other users have to ratifier aparticular action for a particular flag, with regard to a particularphoto. As reflected at 5122, an RRN can be different for differentrequested actions, i.e., for different flags the RRN can be different.For example, a RRN requirement to submit a comment on a photo can beless demanding than an RRN to remove a photo entirely. Additionally, asdescribed above and reflected at 5123, the number of users who areneeded to ratify a particular action, for a particular flag, can dependon the attributes of the user(s) who is doing the ratifying.

With further reference to FIG. 51, each of the data records 5101 includea censorship power rating (CPR), a required ratification number (RRN),and a description of associated processing. For example, if the CPR ofthe nominator is between 0 and 40, then the required ratification numberis 20 in this example. This means that action is performed on the photowith 20 other users ratifying. Such required number of ratifiers can bedecreased if 1 of the ratifiers is a superuser or super ratifier, suchthat his or her ratification is magnified.

For example, if the CPR of the nominator is between 40 and 60, then therequired ratification number is 10 in this example. That is, a CPR of 40to 60 is mapped to a required ratification number of 10. This means thataction is performed on the photo with 10 other users ratifying. As shownin the table 5100, it may be the case that the CPR of the nominator isbetween 80 and 100. Such reflects a very strong nominator. In thissituation, the required ratification number might indeed be 0.Accordingly, no ratification might be required to complete the actionthat is requested by the particular nominator. Accordingly, the numberof ratifying users needed to ratify a particular action (e.g. removal ofa photo) can depend on (a) strength or censorship power rating (CPR) ofthe nominator user, and (b) strength of the ratifying users who canagree or disagree with the nominator. Relatedly such strength of thenominating user and strengths of the ratifying users can be differentfor different flags, i.e. different for different requested actions.Thus, a weak nominating user may require more ratifying users, ascompared with a strong nominating user.

Various features of censorship processing are described above.Censorship processing of the disclosure can include a nomination by oneuser and then ratification by additional users. The additional users caneither follow or not follow the nominator. Successful or unsuccessfulcensorship can be logged into user profiles to determine a censorshippower rating over time, where the censorship power rating gets strongerwith ratification and weaker with negation, as described herein. Thepower rating can be integrated and considered in the nomination andratification processing associated with censorship of a photo.Censorship can include removing a particularly offensive photo, forexample. Censorship can include any of a variety of other action items.Censorship can include corrections to a photo, revisions to a photo,removal or deletion of a photo, or other action items as desired.Censorship processing can address offensive content and/or undesirablecontent and provide a mechanism by which users of the system can controlsuch content. Undesirable content can include sexually suggestivephotos, cruelty, violence, promotion or solicitation, hate ordiscriminating comments, political debate, and/or other offensivecontent and may be reflected in pop-up menus as represented by menu 5214shown in FIG. 52.

FIG. 53 is a schematic diagram showing a user device 5300 with the GUI5330, in accordance with principles of the disclosed subject matter. TheGUI 5330 includes a selection window 5350 that displays selectable tagoptions. The GUI includes a chosen window 5360 that displays chosen tagoptions 5361. The GUI includes a photo selection window 5310. Using thephoto selection window 5310, a user can select a particular photo forprocessing. In this example, a photo 5311 that has been selected isPicture_0101.JPGG. Selection of such photo 5311 can include searchingfor the photo, retrieving the photo from a folder, clicking on the photoin a particular GUI, using a drop-down menu, and/or other mechanism toidentify the particular photo for processing. The selection window 5350includes various tag options 5351, i.e. selectable tag options. Forexample, the window 5350 includes a selected tag 5351′, “Nature scene”.The user can identify that the photo 5311 relates to a nature scene.Accordingly, the user might select the tag 5351′. The user can then tapan add button 5621 in the GUI 5330. Such action results in the “Naturescene” identifier 5361′ being added into the chosen window 5360. Asshown, the tag options winter season and regular lens camera havealready been added into the chosen window 5360. A user may also removeitems from the chosen window 5360. A user can select an item in thechosen window 5360, and tap the delete button 5322. As result, the CPwill remove the selected item from the chosen window 5360. As shown, an“Other” button 5362 can be provided on the GUI 5330. The user can tapthe “Other” button 5362 which allows for the addition of user freeformtag entries. Freeform tag entries can be entered as hashtags and in theexample the user has entered #Deer. Such hashtag is shown in the chosenwindow 5360. Users can enter multiple freeform tags so as to tag aselected picture. The windows 5350 5360 and GUI 5330 of FIG. 53 can alsobe provided with other visual mechanisms and/or selection mechanisms,such as drop down menus.

As shown in FIG. 53, the GUI 5330 can include a home icon 5304 by whicha user can access a landing page of the system. A menu icon 5305 can beprovided. A user can tap the menu icon 5305 so as to access any of avariety of menu options or features as described herein. The user device5300 can also include functional items including a speaker 5301, acamera 5302, and a microphone 5303. A camera can also be provided on theopposing side of the user device 5300. The user device 5300 can includeknown features that can be used in conjunction with the novel featuresof the disclosure.

FIG. 54 is a flowchart showing processing that can be used inconjunction with the GUI 5330 of FIG. 53. The process of FIG. 54 islaunched in step 5400. Such process can be launched, invoked, or calledupon as a result of the user accessing the GUI 5330, for example. TheGUI 5330 can be accessed via a suitable GUI option or menu option, forexample. Once the process is launched, the process passes onto step5402. In step 5402, the CP interfaces with the user device to present atag option on the GUI 5330. The tag option might be “nature scene” or afreeform tag option, which can be created by tapping the “Other” button5362. The freeform tag option can be a “hashtag” such as “#Deer” asdescribed above. The CP can be a server processing component disposed ona network and in communication with user device. In step 5410, theprocessor interfaces with the user device, i.e. interfaces with a user,to select a selectable tag option in the selection window 5350. Then instep 5411, the CP interfaces with the user device to select the addoption 5321. Then in step 5412, the CP transfers the selected tag optionfrom the selection window 5350 to the chosen window 5360. Alternatively,in step 5420, the CP can interface with the user to select a chosen tagoption in the chosen window 5360. In step 5421, the CP interfaces withuser device to select the delete option 5322. Once selected, in step5422, the CP deletes the chosen tag option from the chosen window 5360.Accordingly, the processing of FIG. 54 can be used to enable the GUI5330 of FIG. 53.

Additional features of the disclosure are described below relating to“filtered following” processing. The disclosure provides a methodologythat allows users to accumulate data that can be used to validate orverify data presented by the system of the disclosure. At a high level,users can select a “Location Type” as identified in FIG. 12 (in step613) to filter and tag photos. Photos can be collected into establishedformal “channels” or “channels” of grouped photos.

To explain further, as reflected at 612″ in FIG. 12, processing can beperformed that includes (a) the creation of “channels” and (b) theassociation of photo(s) to a respective channel. The created channelscan be created and stored, as a digital framework, in the databaseportion 120. Accordingly, the system of the disclosure can includeviewable channels of photos. For example, a food channel can be providedthat includes photos tagged with “To Eat” or other food related tags.Other channels might include a “Nature Channel” (containing naturerelated photos) or a “sports channel” (containing sports relatedphotos). As described herein, censorship power ratings may be used inthe processing of the disclosure. Censorship power ratings, as well asother parameters used in the processing of the disclosure, can betracked based upon such channels of photos, i.e. so as to potentially bedifferent (for a given photo) for different channels. Accordingly,parameters can be different for different channels. Censorship powerratings and other parameters can be different for different user groupsthat follow or view certain “channels”. For example, censorshipexpectations based upon mature content, etc., can vary between differentuser groups.

In a more complex example, filtered following processing can be used totest or validate the truth of ratings preferences with regard to aparticular photo or other media content, such as a posting. Filteredfollowing processing allows a user to readily change their perspectiveor viewpoint. The perspective can be seen through different users orthrough different groups of users. Filtered following processing canallow for a user to view the perspective of an established trustedcritic(s), an affinity group, followed users, friends, groups offriends, trusted specialty groups, or other persons or groups, forexample. Processing to achieve such objectives is described below.

FIG. 55 is a flowchart showing filtered following processing, inaccordance with principles of the disclosed subject matter. The filteredfollowing processing of FIG. 55 can be called or invoked utilizing asuitable option presented on a GUI of a user device. For example,filtered following processing could be called upon or invoked as part ofthe processing of step 763 of FIG. 17. The process of FIG. 55 islaunched in step 5500. Upon the filtered following processing beinglaunched, any of the processing of steps 5511, 5512 and 5513 can beperformed as called upon through user interaction with a user, i.e. witha user device.

In step 5511, the CP interfaces with a first user to establish afiltered following (FF) association (i.e. a first FF association)between the first user and respective photos (forming a first collectionof photos), and the first collection of photos can constitute a firstfiltered set of photos, i.e. a first filtered photo set of photos.Details are described below with reference to subroutine 5600 of FIG.56. As reflected at 5512′, the FF associations can be based on who tookthe photo, who liked the photo, tags assigned to a photo, location typeand/or other attribute(s) associated with a photo. The FF associationscan be based on a person or a group. As reflected at 5511′ in FIG. 55, afiltered following (FF) association is described in the context of agroup or collection of photos being associated with a user, such as inthe processing of step 5511 and step 5512. A filtered followingassociation may also be based on an affinity group or other group ofusers. That is, a collection of photos can be based on photos that areassociated with an affinity group or other group of users.

In step 5512 of FIG. 55, the CP interfaces with a second user toestablish a FF association (i.e. a second FF association) between thesecond user and respective photos (forming a second collection ofphotos), and the second collection of photos can constitute a secondfiltered set of photos, i.e. a second filtered photo set of photos.Processing can be similar to subroutine 5600, described above. Ratherthan photos, other media can be processed, such as electronic messagesor other content.

In step 5513, the CP interfaces with a third user to allow the thirduser to (A) select the first user, so as to view the first filteredphoto set, and (B) select the second user, so as to view the secondfiltered photo set.

Processing can be performed so as to compare the two photo sets. Detailsare described below with reference to subroutine 6000 of FIG. 60. Asreflected at 5513 the third user can input or select both the user thatis to be used to perform the filter processing (i.e. a first user whoseperspective will be viewed by the third user) and/or a filter tag thatis to be used in the filter processing. For example, the first filteredphoto set can be based on an association of photos with one or moreusers. For example, the second filtered photo set can be based on anassociation of photos with one or more users. For example, a secondfiltered photo set might be a collection of photos that are associatedwith all users in the system and/or a collection of photos that havebeen input into the system.

FIG. 56 is a flowchart showing details of subroutine 5600 as called fromFIG. 55, in accordance with principles of the disclosed subject matter.The process is launched and can include any of the processing of steps5610, 5620 and 5630. In step 5610, the CP establishes filtered following(FF) association based on photos that were “taken” by the first user.Such processing can include interfacing with the first user, i.e. afirst user device. Subroutine 5700 can be called, as described withreference to FIG. 57 below. In step 5620, the CP interfaces with thefirst user to establish FF association based on photos that were “liked”by the first user. Subroutine 5900 can be called, as described withreference to FIG. 59 below. In step 5630, the CP establishes a filteredfollowing (FF) association based on photos that were “tagged” in aparticular manner by the first user. Subroutine 5900 can be called, asdescribed with reference to FIG. 59 below.

FIG. 57 is a flowchart showing details of “CP establishes filteredfollowing (FF) association based on photos that were “taken” by thefirst user” of subroutine 5700 as called from FIG. 56, in accordancewith principles of the disclosed subject matter. The process of FIG. 57can include interfacing with the first user device, i.e. interfacingwith the first user. The subroutine is launched in step 5700 and passesonto step 5701. In step 5701, the processor retrieves or creates a userID number or other identifying number or identification that isassociated with the first user device, i.e. the first user. Then, instep 5702, the processor inputs photos from the first user device.Alternatively, the processor could retrieve photos from memory or datastore that were previously input from the user. The photos can beassociated with the user via a data association, such as is shown in thedata architecture FIG. 64. Accordingly, in step 5703, the processorassigns the user ID to such photos as the photos are input from the userdevice. The CP can write the user ID to a data record 6422 that is partof the metadata of the photo (see FIG. 64). As reflected at 5703, if thephoto already includes user identifying indicia in the metadata of thephoto, the CP can map such user identifying indicia to a system createduser ID, and insert such system created user ID in data record 6422.Then the process passes onto step 5704.

In step 5704, the system saves the photo, with modified metadata, intoan accessible database of the server—so that the photo can be accessedby other users. Accordingly, as reflected at 5704′ the photo is thussearchable based on the user ID number of the user device that was usedto take the photo. Accordingly, photos in the system can be aggregatedbased on the photographing user, and presented to the third user as afiltered following. Then, in step 5705, the process is terminated, i.e.the subroutine has been completed.

FIG. 58 is a flowchart showing details of “CP establishes filteredfollowing (FF) association based on photos that were “liked” by thefirst user” of subroutine 5800 as called from FIG. 56, in accordancewith principles of the disclosed subject matter. The process of FIG. 58can include interfacing with the first user device, i.e. interfacingwith the first user. The subroutine is launched in step 5800 and passesonto step 5801. In step 5801, the processor receives a request (from athird user) to generate a FF association based on “liked” relationshipof photo with a first user. In step 5802, the processor interfaces withthe third user to input the user name of the first user. The first username can then be mapped to a user ID of the first user. Then, in step5803, the processor identifies data records 6410′ (in photo ID table6410 (FIG. 64)) representing respective photos that contain the ID (ofthe first user) in the “liked” data field 6428. Then in step 5804, theprocessor saves photos that were identified in the search (of step 5803)as a collection of photos, which form a filtered set of photos. Theprocess then passes onto step 5804.

In step 5804, the processor provides the third user with access to thecollection of photos, which form the requested filtered set of photos.Then, in step 5805, the process is terminated, i.e. the subroutine hasbeen completed.

FIG. 59 is a flowchart showing details of “CP establishes filteredfollowing (FF) association based on photos that were “tagged” in aparticular manner by the first user” of subroutine 5900 as called fromFIG. 56, in accordance with principles of the disclosed subject matter.As reflected at 5900′, for example, the particular tagging might bephotos that the first user has tagged as “nature” photos. Such taggingcan be indicative that such tagged photos are favored by the first useras nature photos. Accordingly, a perspective via the first user's eyescan be provided to other users. The processing of FIG. 59 is enabled bythe data content of FIG. 64.

The processing of subroutine 5900 starts in step 59 and passes onto step5901. In step 5901, the processor receives a request, from the thirduser in this illustrative example, to generate a filtered followingassociation based on “tagged” relationship of photos with the firstuser. Then, the process passes onto step 5902. In step 5902, theprocessor interfaces with the third user to input username of the firstuser to be used in the filtered following. Then, the first user name canbe mapped to a user ID of the first user. The CP also interfaces withthe first user to input the particular “tag” (i.e. the FF tag) that isto be used in the requested filtered following. The tag could be“nature” for example. Then, in step 5903, the processor identifies datarecords 6410′ (in photo ID table 6410 (FIG. 64)) representing respectivephotos that (1) have been tagged using the FF tag, and (2) have thefirst user as a “tagger” of such FF tag. For example, the processordetermines if the first user is listed in the data record 6429 in datatable 6420 (FIG. 64).

Then in step 5904, the processor saves photos that were identified inthe search (of step 5903) as a collection of photos, which form afiltered set of photos. The process then passes onto step 5905.

In step 5905, the processor provides the third user with access to thecollection of photos, which form the requested filtered set of photos.Then, in step 5906, the process is terminated, i.e. the subroutine hasbeen completed.

FIG. 60 is a flowchart showing details of “CP interfaces with a thirduser to allow the third user to (A) select the first user, so as to viewthe first filtered photo set, (B) select the second user, so as to viewthe second filtered photo set, AND (C) perform processing to compare thetwo photo sets” of subroutine 6000 as called from FIG. 55, in accordancewith principles of the disclosed subject matter. The subroutine islaunched in step 6000 and passes to Step 6000′. In step 6000′, theprocessor performs subroutine modules in response to request from auser, in this case a user described as a third user. Accordingly, theprocessing provides for any of the modules 6001, 6002 and 6003 to beperformed.

In the module 6001, the CP interfaces with a third user to allow thethird user to select the first user and to select filtered following(FF) association(s), so as to view the first filtered photo set.Subroutine 6100 is called, as described below with reference to FIG. 61.In the module 6002, the CP interfaces with the third user to allow thethird user to select a second user and FF association(s), so as to viewthe second filtered photo set. Module 6002 is provided to reflect thatthe third user can select additional users in filtered followingprocessing. As otherwise described herein, the additional users can beselected so as to allow the third user to view different perspectives.The processing of module 6002 can be similar to the processing describedbelow with reference to module 6001.

In the module 6003, the CP can perform processing to compare the twofiltered photo sets that were generated in modules 6001 and 6002. Moduleor step 6003 can also generate results of the comparison for the thirduser. Module 6003 can be performed by subroutine 6200 as described belowwith reference to FIG. 62. After the desired processing is performed instep 6000′, the process can pass onto step 6004. In step 6004, theprocessor can output the rendered results to the user, here the thirduser.

FIG. 61 is a flowchart showing details of “CP interfaces with a thirduser to allow the third user to select the first user and to selectfiltered following (FF) association(s), so as to view the first filteredphoto set” of subroutine 6100 as called from FIG. 60, in accordance withprinciples of the disclosed subject matter. Relatedly, FIG. 63 shows auser device 6300 displaying a GUI 6330, in accordance with principles ofthe disclosed subject matter. The GUI 6330 is provided to selectfiltered following options.

Note FIGS. 57-59 relate to establishing filtered following associationsbased on input data. On the other hand, FIG. 61 relates to the actualinputting of the data from the user, i.e. and once such data is input,the data can be used in the processing of FIGS. 57-59.

With further reference to FIG. 61, the subroutine is launched in step6200 and passes onto step 6101. In step 6101, the processor interfaceswith the third user to present a GUI such that the third user can selectthe first user, amongst a selection of users, so as to view aperspective of the first user. Such a GUI can be in the form of adrop-down menu to select the first user and/or provide certain selectioncapability to select the first user, for example. The GUI 6330, of FIG.63, can include a user selection option 6331.

The option 6331 allows the third user to tap and search for users, suchas a first and second user for example, to filter follow. Otherselection mechanisms could be utilized as desired. For example, the userselection item 6331 can provide a user with the ability to select agroup of users to filter follow. The group of users, which may beselected, may be an affinity group; “friends”; or “users followed,” forexample. Accordingly, a user can be selected, i.e. the “first user” isselected for purposes of this description. After step 6101, the processpasses onto step 6102. In step 6102, the processor interfaces with thethird user to select filtered following (FF) association(s) that areavailable. As noted at 6102′, the filtered following associations caninclude (1) association based on photos taken by a first user, (2)association based on photos “liked” by a first user, and/or (3)association based on photos that were tagged by the first user with aparticular tag. More specifically, with regard to the association basedon tags, note related step 5902 of FIG. 59. The processor can interfacewith the user to input the filtered following (FF) options via the firstFF option 6332, the second FF option 6333, and/or the third FF option6334, as shown in the GUI 6330 of FIG. 63. Various other FF options canbe provided for selection by the user. Indeed all the photos that areavailable to the user and/or all the photos that are on the system (andsatisfy selected criteria), for example, can be provided as an FFoption.

With further reference to FIG. 61, after step 6102, the process passesonto step 6103. In step 6103, the processor interfaces with the thirduser to select constraints that the third user wants to impose upon thefiltered following. Note at 6103′, constraints can include geographicalconstraints, time constraints, or other constraints as may be desired.Such constraints can be selected and imposed upon the filtered followingso as to limit photos contained and presented to the third user in thefiltered following. For example, such a constraint can be selected bythe third user utilizing the Geo option 633 of the GUI 6330 of FIG. 63.With such Geo option 6335, the third user has limited the photos to theparticular geographical area of New York City. As noted at 6330′, anoption or selection of the GUI 6330 (FIG. 63) can be presented in theform of a window, buttons, radio buttons, checkboxes, group boxes,dialogue boxes and other user interface mechanisms. The GUI 6330 canalso provide a zoom option 6336. The zoom option allows the third userto render results of the filtered following to a particular zoom leveland/or to particular longitude-latitude coordinates, for example.Additionally, the GUI 6330 includes an add user option 6337. Such optionallows the third user to select additional users for an additionalfiltered following. Filtered followings can be generated and comparedbetween two or more different users. Also, a filtered following can begenerated and viewed in and of itself.

FIG. 67 is a representation of a GUI 6700, in accordance with principlesof the disclosed subject matter. The GUI 6700 can include various“filter” icons 6701 for selection by a user, e.g. the “third” user asdescribed herein. By tapping on one of the displayed filter icons 6701,a user can access a previously set up filtered following. Also, adisplayed filter icon 6701 can be mapped to a traditional filter. Such atraditional filter could include a filter that renders only “city”photos, for example, from a collection of photos. Such a traditionalfilter is distinct from the filtered following processing as describedherein. The filters of GUI 6700 can be enabled to be scrolled left andright—by the user “swiping” their finger—so as to “roll” throughdifferent filters. Accordingly, by swiping in the area 6710, the usercan access more filters. As many filters can be provided as may bedesired.

After step 6103, the process passes onto step 6104. In step 6104, theprocessor can interface with the third user to output the results basedon the first user selection, selection of the FF association(s), and anyparticular constraints imposed. Then, in step 6105, the subroutine isterminated. As reflected at 6300T in FIG. 63, the GUI of FIG. 63 can begenerated in response to a user tapping the filter button 6701 in FIG.67, for example.

FIG. 62 is a flowchart showing details of “processor performs processingto compare two filtered photo sets, and to generate results of thecomparison to be output to the third user” of subroutine 6100 as calledfrom FIG. 60, in accordance with principles of the disclosed subjectmatter. The subroutine can be launched and pass onto step 6200′. In step6200′, various modules can be provided so as to be selectable by a user,in this example the third user. In general, it is appreciated thatfiltered following processing that generates a filtered following canrelate to a single user. That is, the third user can select a first userwhose perspective the third user wishes to observe. However, differentfiltered followings can be performed so as to generate differentfiltered photo sets. These different filtered photo sets can then becompared. For example, a user might just mentally compare differentfiltered photo sets by viewing one set and then viewing the other set.However, processing functionality can also be provided so as to comparedifferent filtered photo sets. FIG. 62 relates to such processingfunctionality.

FIG. 62 shows the processing module 6201. In processing of such module,the processor interfaces with the third user to display photos that areincluded in both the first filtered set of photos (associated with thefirst user) AND the second filtered set of photos (associated with thesecond user). FIG. 62 also shows processing module 6202. In processingof such module, the processor interfaces with the third user to displayphotos that are included in the first and second filtered sets ofphotos, as well as provides functionality to constrain or limit thedisplay based on geo-location (i.e. geographical location), time period,and/or other constraint. FIG. 62 also shows processing module 6203. Inprocessing of such module, the processor interfaces with the third userto display photos that are included in the first and second filteredsets of photos, as well as additional sets of photos from further users.After a module of step 6200 is selected, the process passes onto step6204. In step 6204, the processor displays results of the selectedcomparison to the third user. For example, pins (that represent photos)could be color coded so as to indicate which user the particular pin isassociated with. Other graphical distinctions could be used. Then, theprocess passes onto step 6205. In step 6205, the processing isterminated. That is, the subroutine is completed. It is appreciated thatcomparison processing and other processing related to generated filteredphoto sets are not limited to the particular processing shown in FIG.62. Various other functionality and processing can be provided. In theprocessing of step 6200′ of FIG. 62, the first and second filtered setsof photos can be presented (for comparison by a user) (a) on respectivefirst and second screens that are adjacent to each other or (b) on thesame screen. Pins, with photo count, representing photos can bedisplayed. Pins can be selectively displayed so as to reflect only moredense areas. For example, if viewing at the “local” level, displayedpins might only represent the top 10 patches in any local area beingdisplayed—so as to reflect the top 10 highest points of interest in aparticular local area being displayed. Other features can be provided soas to give a user comparison ability. For example, a group of pins mightbe selected so as to be aggregated or displayed collectively in somemanner.

However, as noted above, a filtered following can be generated andviewed in and of itself. That is for example, the processing of step6200′ of FIG. 62 can also include a request to view only one set offiltered photos. That is, the illustrative “third user” can request,through interfacing with the CP (processor), a first filtered set ofphotos that is associated with a first user. Such processing isillustrated in FIG. 61, for example. The third user can then view suchfiltered following, so as to look though the perspective or “lens”,metaphorically speaking, of the first user. Such processing can be apowerful tool in and of itself. Such processing can provide the user(e.g. the third user) with the ability to “see what you want to see” andthe ability to filter out what the third user does not want to see. Suchfiltered following processing can provide for filtering media contentbased on user perspective, that can be for editing, viewing, comparison,validation and voting, for example. Thus, in such processing andimplementation, there might not be comparison between different filteredsets of photos, but viewing of one filtered set of photos individually.

FIG. 64 is a schematic diagram showing data content 123C, in accordancewith principles of the disclosed subject matter. For example, the datacontent 123C could be contained in the photo database 123 shown inFIG. 1. The data content of FIG. 64 can include a photo ID table 6410and a photo data table 6420. The photo ID table 6410 can include aplurality of data records 6410′. Each of the data records 6410′ caninclude a photo ID number. For example, the data record 6411 can includethe photo ID number PH12341234. The photo ID table 6410 is searchable bya user. Each of the photo ID numbers can be linked, mapped or otherwiseassociated to a photo data table. As result, a user can access arespective photo data table for data regarding a particular identifiedphoto. The data content of FIG. 64 shows that the data record 6411 islinked to the photo data table 6420, in this illustrative example. Asshown, the photo data table 6420 can contain photo data. The photo datacan contain image data and various metadata in respective data fields,as reflected at 6401.

The photo data table 6420 can include data records 6420′. Each datarecord 6420′ can include a name field 6420N and a value field 6420V. Thephoto data table 6420 can include the photo ID number in a photo ID datarecord 6421. Such data record can be linked to the photo ID table 6410.The table 6420 can include data record 6422. The data record 6422 caninclude user ID of the user that took the particular photo. Data recordscan be provided that contain the photo date and the photo time. Thelocation data record 6425 can include photo location. The location datarecord 6425 can be linked to data structure 6450. The data structure6450 can contain data regarding the photo location, in addition to thedata contained in data record 6425. In this case, the photo location isillustratively Times Square in New York City. Data record 6426 caninclude the image data. For example, such data can be in the form of aJPEG file that represents the actual picture or photograph that wastaken. The data record 6427 can include a variable indicating whetherfiltered following is enabled or not enabled for the particular photo,e.g. whether filtered following is enabled as to the particular photo.Such selection can control whether or not certain functionality isprovided with regard to the particular photo. A liked data record 6428can contain the user IDs of those users who “liked” the particularphoto.

The photo data table 6420 can include various tag data records 6420′.One of these can be tag data record 6429. As described above, processingcan include identifying a data record 6410′ (in photo ID table 6410 ofFIG. 64) that represents a photo that (1) has been tagged using aparticular filtered following (FF) tag, and (2) has a first user as a“tagger” of such FF tag. For example, the processor can determine if thefirst user is listed in the data record 6429 in data table 6420, orassociated with the data record 6429 by virtue of being included in datastructure 6440. As described above, the “first user” has been describedas a user that the “third user” chooses to select, to perform a filteredfollowing. To explain further as noted at 6402 of FIG. 64, the tag datarecord 6429 can be linked to data structure 6440. The data structure6440 can contain the list of users that tagged the particular photo witha particular tag. It is this list of users that can be searched infiltered following processing (step 5903 of FIG. 59). The data table6420 can be expanded (to add more tag data records) as more tag datafields are needed to represent additional tags being associated with theparticular photo. Accordingly, one or more users, i.e. first users, canbe associated with a first filtered photo set or photo collection. Anassociation can be constituted by a user tag associated with the one ormore first users being determined to match a respective photo tagassociated with each of the photos in a collection of photos. The phototag can represent or reflect a group of users to which photos in thefirst filtered photo set are associated, and the user tag can provide anassociation between the one or more first users and the group (see FIG.64 and data structure 6440 and tag data record 6429). The group of userscan be in the form of an affinity group that represents an affinity toparticular subject matter. The group can be in the form of a friendsgroup that represents a group of friends. The photo tag can designate apreference, and the user tag represents such same preference, such thatthe photo tag and the user tag are deemed to match and/or the photo tagand the user tag can be determined to be linked to or associated withthe same tag.

Accordingly, the data content of FIG. 64 provides storage and access toa variety of data used in filtered following processing. The datacontent of FIG. 64 can also be used in a wide variety of otherprocessing as described herein.

An example of filtered following may be where the user desires tocompare the top 10 photo locations of a selected geographical area suchas New York City. In such comparison, the user may desire to compare ofthe entire Photer user population (i.e. the entire photo collection ofthe system) vis-à-vis the user's group of friends. Or, for example, theentire photo collection may be compared to a particular affinity groupto which the user belongs. The system as described herein may bedescribed as the “Photer” system.

First Set of Illustrative Embodiments

Embodiment 1. An apparatus to process digital photos, the apparatusincluding a tangibly embodied computer processor (CP) and a tangiblyembodied database, the CP implementing instructions on a non-transitorycomputer medium disposed in the database, and the database incommunication with the CP, the apparatus comprising: (A) a communicationportion for providing communication between the CP and an electronicuser device; (B) the database that includes the non-transitory computermedium, and the database including the instructions, and (C) the CP, andthe CP performing processing including: (a) segmenting an area, into aframework, including advancing across the area to assign areaidentifiers, to remote areas, and respective boundaries that areassociated with the area identifiers of each remote area, and thesegmenting being performed in the form of a row in a given geo-area, andupon reaching an end of a given row, dropping down so as to segment anext row; (b) inputting a photo from a user device, and the photoincluding geo-data that represents a photo location at which the photowas generated; (c) determining that the photo location is within a firstremote area, of the remote areas, (d) determining that there is not anexisting patch area to which the photo can be assigned; and (e) buildingout the framework including adding a first patch area, associating thefirst photo with the first patch area, and orienting the first patcharea within the first remote area, thereby orienting the first photo inthe framework.

Embodiment 2. The apparatus of embodiment 1, the determining that thephoto location is within the first remote area, of the remote areas,being performed using global positioning system (GPS) based on longitudeand latitude of the first photo.

Embodiment 3. The apparatus of embodiment 1, the CP performingprocessing further including generating intermediate areas so as toorient the first patch area within the first remote area.

Embodiment 4. The apparatus of embodiment 3, the intermediate areasincluding territory, sector, quadrant, and local areas, and suchintermediate areas disposed between the first remote area and the firstpatch.

Embodiment 5. The apparatus of embodiment 1, the CP performingprocessing further including generating a second patch area based oncoordinates that are associated with the first patch.

Embodiment 6. The apparatus of embodiment 1, the first remote arearepresented by a first area identifier.

Embodiment 7. The apparatus of embodiment 6, the first area identifierincluding specific digits that represent the first remote area.

Embodiment 8. The apparatus of embodiment 7, the first area identifierincluding specific characters that represent the first patch.

Embodiment 9. The apparatus of embodiment 8, the first remote areafurther including a second patch, and the second patch being adjacent tothe first patch, and the second patch represented by a second areaidentifier, and the second area identifier being sequential relative tothe first area identifier.

Embodiment 10. The apparatus of embodiment 9, the first area identifierand the second area identifier are both respective integers that aresequential in numbering, so as to represent that the first patch isadjacent to the second patch.

Embodiment 11. The apparatus of embodiment 8, the area identifierincluding a plurality of digits, which respectively represent subareaswithin the first remote area.

Embodiment 12. The apparatus of embodiment 11, wherein there are 6 areasrepresented by the area identifier, and the 6 areas including the firstremote area and the first patch area, and the area identifier includesat least 14 characters.

Embodiment 13. The apparatus of embodiment 1, the CP performingprocessing including: generating a photo count of photos in the firstpatch, including the first photo.

Embodiment 14. The apparatus of embodiment 1 the CP performingprocessing including: (a) interfacing with a second user device via thecommunication portion; (b) inputting user geolocation data from thesecond user device; (c) comparing the user geolocation data withlocation data of the first patch; (d) determining that the usergeolocation data matches with the location data of the first patch; and(e) assigning a second photo, taken with the second user device, to thefirst patch based on the determining that the user geolocation datamatches with the location data of the first patch.

Embodiment 15. The apparatus of embodiment 1, the given geo-area is theworld so that the world is segmented into remote areas.

Embodiment 16. The apparatus of embodiment 1, the dropping down so as tosegment a next row includes: advancing in the same direction in rows inconjunction with generating a plurality of remote areas in a given row,OR going back and forth in rows in conjunction with generating aplurality of remote areas in a given row.

Embodiment 17. An apparatus to process media items, the apparatusincluding a tangibly embodied computer processor (CP) and a tangiblyembodied database, the CP implementing instructions on a non-transitorycomputer medium disposed in the database, and the database incommunication with the CP, the apparatus comprising: (A) a communicationportion for providing communication between the CP and an electronicuser device; (B) the database that includes a non-transitory computermedium, and the database including the instructions, and (C) the CP, andthe CP performing processing including: (a) segmenting an area, into aframework, including advancing around the area to assign areaidentifiers, to remote areas, and respective boundaries that areassociated with the area identifiers of each remote area, and thesegmenting being performed in the form of a row in a given geo-area, andupon reaching an end of a given row, dropping down so as to segment anext row; (b) inputting a media item from a user device, and the mediaitem including geo-data that represents a media item location at whichthe media item was generated; (c) determining that the media itemlocation is within a first remote area, of the remote areas, (d)determining that there is not an existing patch area to which the mediaitem can be assigned; (e) building out the framework including adding afirst patch area, associating the first media item with the first patcharea, and orienting the first patch area within the first remote area,thereby orienting the first media item in the framework.

Embodiment 18. The apparatus of embodiment 17, the media item is a photoor an electronic message.

Second Set of Illustrative Embodiments

Embodiment 1. An apparatus to process digital photos, the apparatusincluding a tangibly embodied computer processor (CP) and a tangiblyembodied database, the CP implementing instructions on a non-transitorycomputer medium disposed in the database, and the database incommunication with the CP, the apparatus comprising: (A) a communicationportion for providing communication between the CP and electronic userdevices; (B) the database that includes the non-transitory computermedium, and the database including the instructions, and the databaseincluding a framework that includes a plurality of areas, and theplurality of areas includes a plurality of patches, and the plurality ofpatches includes a first patch; (C) the CP, and the CP performingprocessing including: (1) inputting a first photo from a first user, andthe first photo including first photo data, and the first photo dataincluding (a) image data, and (b) geo-data, in metadata, that representsa photo location at which the first photo was generated; (2) comparingthe geo-data of the first photo with the framework; (3) determining,based on the comparing, that the photo location is in the first patch;(4) associating, based on the determining, the first photo with thefirst patch; (5) incrementing a photo count of the first patch based onthe associating of the first photo with the first patch, and the photocount reflecting popularity of the first patch; and (6) outputting thephoto count to a second user; and wherein (a) the first user includes afirst electronic user device, and (b) the second user includes a secondelectronic user device.

Embodiment 2. The apparatus of embodiment 1, the CP performingprocessing including comparing the photo count of the first patch with apredetermined threshold; determining that the photo count of the firstpatch exceeds the predetermined threshold; and based, on suchdetermining, designating the first patch as a first spot so as to enablerecognition status of the first patch.

Embodiment 3. The apparatus of embodiment 2, the recognition status ofthe first patch includes identifying the first patch in search results,provided to a user, based on the designation of the first patch as aspot.

Embodiment 4. The apparatus of embodiment 1, the framework is acascading framework, and the first patch is part of the cascadingframework.

Embodiment 5. The apparatus of embodiment 4, the first patch, of theplurality of patches, is a lowest level of the cascading framework.

Embodiment 6. The apparatus of embodiment 1, the first patch, of theplurality of patches, is identified by a unique identifier.

Embodiment 7. The apparatus of embodiment 6, the framework is acascading framework; and the unique identifier includes a plurality ofdigits and, of the plurality of digits, respective digits are designatedto represent respective areas that are associated with the first patchin the cascading framework.

Embodiment 8. The apparatus of embodiment 1, the CP performing furtherprocessing including: (a) interfacing with a third user, which includesa third user device, via the communication portion; (b) inputting searchrequest data from the third user; (c) comparing the search request datawith photo data of photos in the plurality of areas in the framework;and (d) outputting, based on such comparing of the search request datawith photo data, photo search results to the third user, and the photosincludes the first photo, and the photo data includes the first photodata.

Embodiment 9. The apparatus of embodiment 8, the outputting the photosearch results includes determining a viewport area being displayed onthe third user device.

Embodiment 10. The apparatus of embodiment 9, the outputting theviewport area relating to a degree of zoom being displayed on the thirduser device.

Embodiment 11. The apparatus of embodiment 9, the outputting the photosearch results includes performing pin placement processing, and the pinplacement processing including: generating pins, for placement in theviewport area, based on density of photos in the viewport area.

Embodiment 12. The apparatus of embodiment 11, the generating pins, forplacement in the viewport area, being further based on an expandedsearch bounds area that extends around the viewport area.

Embodiment 13. The apparatus of embodiment 12, the generating pins, forplacement in the viewport area, further including: (a) identifying thatphotos in the expanded search bounds area support generation of afurther pin in the expanded search bounds area; and (b) moving arepresentation of the further pin into the viewport area so as toviewable on the third user device.

Embodiment 14. The apparatus of embodiment 11, the generating pins, forplacement in the viewport area, including generating a first pin, andthe first pin based on photos in a first local area, and the first localarea positioned at least in part in the viewport area.

Embodiment 15. The apparatus of embodiment 14, the first pin includingindicia that conveys a number of photos in the first local area.

Embodiment 16. The apparatus of embodiment 14, the generating pinsincluding placing the first pin in a center of the first local area.

Embodiment 17. The apparatus of embodiment 14, the first local areaincluding a plurality of patches in the first local area, and thegenerating pins including placing the first pin based on respectivephoto density in the plurality of patches, such that the first pin isplaced, in the first local area, so as to be positioned in a highestdensity patch, of the plurality of patches, and the highest densitypatch having highest photo density, of the parches, in the first localarea.

Embodiment 18. The apparatus of embodiment 1, wherein a plurality ofpatches being the smallest area of the framework, and (a) patches aregenerated, by the CP, in the framework based on at least one selectedfrom the group consisting of: a predetermined known area, a popularlocation, a venue, an attraction, a Zip code, and a voting ward; and (b)the first photo data includes a type of photo and other attributes ofthe first photo in the metadata of the first photo.

Embodiment 19. The apparatus of embodiment 1, the first patch beingassociated with a corresponding attraction, such that the popularity ofthe first patch corresponds to popularity of the correspondingattraction, such that the photo count of the first patch constitutesvotes for the first patch, and the CP performing processing furtherincludes comparing the photo count of the first patch with respectivephoto counts of other patches to determine relative popularity.

Embodiment 20. An apparatus to process digital media, the apparatusincluding a tangibly embodied computer processor (CP) and a tangiblyembodied database, the CP implementing instructions on a non-transitorycomputer medium disposed in the database, and the database incommunication with the CP, the apparatus comprising: (A) a communicationportion for providing communication between the CP and electronic userdevices; (B) the database that includes a non-transitory computermedium, and the database including the instructions, and the databaseincluding a framework that includes a plurality of areas, and theplurality of areas includes a plurality of patches, and the plurality ofpatches includes a first patch; (C) the CP, and the CP performingprocessing including: (1) inputting a first media from a first user, andthe first media including first media data, and the first media dataincluding (a) content data, and (b) geo-data, in metadata, thatrepresents a media location at which the first media was generated, andthe first media data can be text; (2) comparing the geo-data of thefirst media with the framework; (3) determining, based on the comparing,that the media location is in the first patch; (4) associating, based onthe determining, the first media with the first patch; (5) incrementinga media count of the first patch based on the associating of the firstmedia with the first patch, and the media count reflecting popularity ofthe first patch; and (6) outputting the media count to a second user;and wherein (a) the first user includes a first electronic user device,and (b) the second user includes a second electronic user device.

Third Set of Illustrative Embodiments

Embodiment 1. An apparatus to process digital photos, the apparatusincluding a tangibly embodied computer processor (CP) and a tangiblyembodied database, the CP implementing instructions on a non-transitorycomputer medium disposed in the database, and the database incommunication with the CP, the apparatus comprising: (A) a communicationportion for providing communication between the CP and a plurality ofuser devices, the plurality of user devices including a first userdevice (UD) and a second UD; (B) the database that includes thenon-transitory computer medium, and the database including theinstructions, and (C) the CP, and the CP performing processingincluding: (I) storing a photo in the database; (II) outputting thephoto to the first UD, i.e. first user device, for display on the firstUD; (III) providing a flag selector to the first UD in conjunction withthe outputting of the photo to the first UD, and the flag selectorrelating to treatment of the photo, and the flag selector including atleast one flag option; (IV) inputting selection of a flag option, of theat least one flag option, from the first UD, such that the first UDconstitutes a nominator UD, and the flag option is associated with anaction; (V) performing, in response to selection of the flag option,ratification processing, and the ratification processing, performed bythe CP, including: (1) interfacing with the second UD, i.e. second userdevice, to input a ratification of the action, such that the second UDconstitutes a ratifier, and the input ratification constitutes an inputdisposition to the action that has been nominated; (2) incrementing anaccumulated ratification number (ARN) based on the ratification, so asto provide a tally of ratifications that are accumulated; (3) comparingthe ARN with a required ratification number (RRN) to determine if theRRN is satisfied; and (4) rendering a determination, based on thecomparing, including: (a) if the RRN is satisfied by the ARN, performingthe action, OR (b) if the RRN is NOT satisfied by the ARN, notperforming the action and waiting for further ratifications; and (VI)wherein the first user device is associated with and representative of afirst human user, and the second user device is associated with andrepresentative of a second human user.

Embodiment 2. The apparatus of embodiment 1, the CP rendering thedetermination (b) based on that the RRN is not satisfied; and (A) theratification processing further including interfacing with a third UD,i.e. third user device, to input a negation of the action, and suchthird UD constitutes a second ratifier; and (B) decrementing theaccumulated ratification number (ARN) based on the negation, so as toupdate the tally of ratifications accumulated.

Embodiment 3. The apparatus of embodiment 2, the ratification processingfurther including (a) interfacing with a fourth UD to input a furtherratification of the action, and such fourth UD constitutes a fourthratifier; (b) incrementing the accumulated ratification number (ARN)based on the further ratification, so as to further update the tally ofratifications that is accumulated; (c) comparing the updated ARN withthe required ratification number (RRN) to determine if the RRN issatisfied; (d) determining that the RRN is satisfied; and (e)performing, based on that the RRN is satisfied, the action.

Embodiment 4. The apparatus of embodiment 2, the ratification processingfurther including interfacing with a fourth UD to input a further inputdisposition of the action, and the further input disposition being oneof: (a) a ratification of the nominated action; (b) a negation of thenominated action; and (c) an ignoring to the nominated action.

Embodiment 5. The apparatus of embodiment 2, the nominated action beingone of censorship and quarantine.

Embodiment 6. The apparatus of embodiment 1, the RRN constituting athreshold number; and (a) the CP performing further processing includingdetermining that a sufficient number of users have negated the inputselection of the flag option so that the ARN has fallen below apredetermined threshold, and (b) terminating, based on such determining,the ratification processing.

Embodiment 7. The apparatus of embodiment 1, the flag option includes aphoto removal option, and the action includes removing the photo, froman accessible collection of photos, once the RRN has been satisfied.

Embodiment 8. The apparatus of embodiment 1, the performing processingincluding inputting the photo from a third UD and, subsequently, storingthe photo in the database.

Embodiment 9. The apparatus of embodiment 1, the inputting selection ofthe flag option is performed in conjunction with inputting text, and thetext is displayed with the flag option.

Embodiment 10. The apparatus of embodiment 9, the flag option isproposed removal of the photo and the text is an explanation why thephoto should be removed.

Embodiment 11. The apparatus of embodiment 1, the flag option isprovided, to the first UD, as a menu option for display on the first UD.

Embodiment 12. The apparatus of embodiment 1, the first UD is a firstsmart phone, and the second UD is a second smart phone.

Embodiment 13. The apparatus of embodiment the photo includinggeographic data that represents a photo location at which the photo itemwas generated, and the photo is one of a collection of photos that arestored in the database.

Embodiment 14. The apparatus of embodiment 1, the ratificationprocessing further including determining a censorship power rating (CPR)that is associated with the first UD, and the CPR being an adjuster thatadjusts the RRN, such that number of ratifiers required to effect theaction can be adjusted up or adjusted down, and (a) the RRN and/or theCPR is flag specific so as to be different for different flags.

Embodiment 15. The apparatus of embodiment 1, the flag selector is inthe form of a button that is presented, by data output by the CP to thefirst UD, on a GUI of the first user device.

Embodiment 16. The apparatus of embodiment 1, the at least one flagoption includes at least one selected from the group consisting of acorrect photo option, a revise photo option, a remove photo option and atag photo option.

Embodiment 17. An apparatus to process media items, the apparatusincluding a tangibly embodied computer processor (CP) and a tangiblyembodied database, the CP implementing instructions on a non-transitorycomputer medium disposed in the database, and the database incommunication with the CP, the apparatus comprising: (A) a communicationportion for providing communication between the CP and a plurality ofuser devices, the plurality of user devices including a first userdevice (UD) and a second UD; (B) the database that includes anon-transitory computer medium, and the database including theinstructions, and (C) the CP, and the CP performing processingincluding: (I) storing a media item in the database; (II) outputting themedia item to the first UD for presentation on the first UD; (III)providing a flag selector to the first UD in conjunction with theoutputting of the media item to the first UD, and the flag selectorrelating to treatment of the media item, and the flag selector includingat least one flag option; (IV) inputting selection of a flag option, ofthe at least one flag option, from the first UD, such that the first UDconstitutes a nominator UD, and the flag option is associated with anaction; (V) performing, in response to selection of the flag option,ratification processing, and the ratification processing, performed bythe CP, including: (1) interfacing with the second UD to input aratification of the action, such that the second UD constitutes aratifier, and the input ratification constitutes an input disposition tothe action that has been nominated; (2) incrementing an accumulatedratification number (ARN) based on the ratification, so as to provide atally of ratifications that are accumulated; (3) comparing the ARN witha required ratification number (RRN) to determine if the RRN issatisfied; and (4) rendering a determination, based on the comparing,including: (a) if the RRN is satisfied by the ARN, performing theaction, OR (b) if the RRN is NOT satisfied by the ARN, not performingthe action and waiting for further ratifications.

Embodiment 18. The apparatus of embodiment 15, the media item is aphoto.

Fourth Set of Illustrative Embodiments

Embodiment 1. An apparatus to process digital photos, the apparatusincluding a tangibly embodied computer processor (CP) and a tangiblyembodied database, the CP implementing instructions on a non-transitorycomputer medium disposed in the database, and the database incommunication with the CP, the apparatus comprising: (A) a communicationportion for providing communication between the CP and a plurality ofuser devices; (B) the database that includes the non-transitory computermedium, and the database including the instructions and a framework forstoring a collection of photos, and (C) the CP, and the CP performingprocessing including: (1) storing the collection of photos, and eachphoto, in the collection of photos, including (a) image data and (b)metadata; (2) interfacing with one or more first users to identify afirst association between the one or more first users and respectivephotos in a first collection of photos, and the first collection ofphotos constituting a first filtered photo set of photos; (3)interfacing with one or more second users to identify a secondassociation between the one or more second users and respective photosin a second collection of photos, and the second collection of photosconstituting a second filtered photo set of photos; and (4) interfacingwith a third user to allow the third user to select the one or morefirst users, so as to view the first filtered photo set; (5) interfacingwith the third user to allow the third user to select the one or moresecond users, so as to view the second filtered photo set; (6) wherebythe third user is provided with access to different filtered photo setsthat are representative of (a) a one or more first users perspective ofthe one or more first users as represented by the first filtered photoset, and (b) a one or more second users perspective of the one or moresecond users as represented by the second filtered photo set; and (D)wherein the one or more first users, the one or more second users, andthe third user each include a respective user device; and the first andsecond collection of photos is of the collection of photos.

Embodiment 2. The apparatus of embodiment 1, the first association isconstituted by that the one or more first users took each of the photosin the first collection of photos; and the second association isconstituted by that the one or more second users took each of the photosin the second collection of photos.

Embodiment 3. The apparatus of embodiment 2, the first filtered photoset and the second filtered photo set are from a same geographical area.

Embodiment 4. The apparatus of embodiment 1, the first association isconstituted by that the one or more first users liked each of the photosin the first collection of photos; and the second association isconstituted by that the one or more second users liked each of thephotos in the second collection of photos.

Embodiment 5. The apparatus of embodiment 4, the first filtered photoset and the second filtered photo set are from a same geographical area.

Embodiment 6. The apparatus of embodiment 1, the first association isconstituted by a user tag associated with the one or more first usersbeing determined to match a respective photo tag associated with each ofthe photos in the first collection of photos.

Embodiment 7. The apparatus of embodiment 6, the photo tag represents agroup to which photos in the first filtered photo set are associated,and the user tag provides an association between the one or more firstusers and the group.

Embodiment 8. The apparatus of embodiment 7, the group of users is inthe form of an affinity group that represents an affinity to particularsubject matter.

Embodiment 9. The apparatus of embodiment 7, the group is in the form ofa friends group that represents a group of friends.

Embodiment 10. The apparatus of embodiment 6, the photo tag designates apreference, and the user tag represents such same preference, such thatthe photo tag and the user tag are deemed to match.

Embodiment 11. The apparatus of embodiment 6, each photo tag representsa geographical location.

Embodiment 12. The apparatus of embodiment 6, each photo tag representsan attribute of the photo, and the attribute including at least oneselected from the group consisting of lens type, time of day, location,scene type, and season of the year.

Embodiment 13. The apparatus of embodiment 1, the CP performingprocessing includes: (a) determining that a first photo (a) is in thefirst filtered photo set of photos and (b) IS in the second filteredphoto set of photos; (b) determining that a second photo (a) is in thefirst filtered photo set of photos and (b) IS NOT in the second filteredphoto set of photos; (c) deeming that a following strength of the firstphoto is greater that a following strength of the second photo based on(a) and (b).

Embodiment 14. The apparatus of embodiment 1, the first filtered photoset and the second filtered photo set are from a first geographicalarea; and the third user being provided with access to the firstfiltered photo set and the second filtered photo allows the user toperform validation of information regarding the first geographical area.

Embodiment 15. The apparatus of embodiment 14, the validation ofinformation regarding the first geographical area relates to popularityof the first geographical area.

Embodiment 16. The apparatus of embodiment 1, the one or more firstusers is a single user, and the one or more second users is a furthersingle user.

Embodiment 17. An apparatus to process digital photos, the apparatusincluding a tangibly embodied computer processor (CP) and a tangiblyembodied database, the CP implementing instructions on a non-transitorycomputer medium disposed in the database, and the database incommunication with the CP, the apparatus comprising: (A) a communicationportion for providing communication between the CP and a plurality ofuser devices; (B) the database that includes a non-transitory computermedium, and the database including the instructions and a framework forstoring a collection of photos, and (C) the CP, and the CP performingprocessing including: (1) storing the collection of photos, and eachphoto, in the collection of photos, including (a) image data and (b)metadata; (2) interfacing with one or more first users to identify afirst association between the one or more first users and respectivephotos in a first collection of photos, and the first collection ofphotos constituting a first filtered photo set of photos; (3)identifying a second collection of photos that have been input into thesystem, and the second collection of photos constituting a secondfiltered photo set of photos; and (4) interfacing with a third user toallow the third user to select the one or more first users, so as toview the first filtered photo set; (5) interfacing with the third userto allow the third user to view the second filtered photo set; (6)whereby the third user is provided with access to different filteredphoto sets that are representative of (a) a one or more first usersperspective of the one or more first users as represented by the firstfiltered photo set, and (b) a one or more second users perspective ofone or more second users as represented by the second filtered photoset; and (D) the one or more first users, the one or more second users,and the third user each include a respective user device; and (E) thefirst and second collection of photos is of the collection of photos.

Embodiment 18. The apparatus of embodiment 17, the second collection ofphotos is constituted by one of: (a) photos, which possess a firstattribute, (b) photos, which possess a second attribute, that areaccessible by the third user, and (c) photos, which possess a thirdattribute, that are accessible by the third user, and wherein: (1) thefirst attribute is accessibility by the third user; (2) the secondattribute reflects that each photo, in the second collection of photos,were each taken in a same geographical area, and (3) the third attributereflects that each photo, in the second collection of photos, were eachtaken by a same user; and (4) wherein, the one or more first usersincludes at least one selected from the group consisting of: anindividual, group of users, trusted critics group, an affinity group,followed users, friends, groups of friends, trusted specialty groups,persons, and groups. Embodiment 19. An apparatus to process digitalmedia, the apparatus including a tangibly embodied computer processor(CP) and a tangibly embodied database, the CP implementing instructionson a non-transitory computer medium disposed in the database, and thedatabase in communication with the CP, the apparatus comprising: (A) acommunication portion for providing communication between the CP and aplurality of user devices; (B) the database that includes anon-transitory computer medium, and the database including theinstructions and a framework for storing a collection of media, and (C)the CP, and the CP performing processing including: (1) storing thecollection of media, and each media, in the collection of media,including (a) content data and (b) metadata; (2) interfacing with one ormore first users to identify a first association between the one or morefirst users and respective media in a first collection of media, and thefirst collection of media constituting a first filtered media set ofmedia; (3) identifying a second collection of media that have been inputinto the system, and the second collection of media constituting asecond filtered media set of media; and (4) interfacing with a thirduser to allow the third user to select the one or more first users, soas to view the first filtered media set; (5) interfacing with the thirduser to allow the third user to view the second filtered media set; (6)whereby the third user is provided with access to different filteredmedia sets that are representative of (a) a one or more first usersperspective of the one or more first users as represented by the firstfiltered media set, and (b) a one or more second users perspective ofone or more second users as represented by the second filtered mediaset; and (D) the one or more first users, the one or more second users,and the third user each include a respective user device; and the firstand second collection of media is of the collection of media.

Embodiment 20. The apparatus of embodiment 19, the media includesphotos, and the content data for each photo includes data representing aphotograph.

Hereinafter, further aspects of the disclosure will be described.

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As used herein, any term in the singular may be interpreted to be in theplural, and alternatively, any term in the plural may be interpreted tobe in the singular.

It is appreciated that one or more features of one embodiment of thedisclosure as described herein may be used in conjunction with featuresof one or more other embodiments as may be desired.

Hereinafter, further aspects of implementation of the systems andmethods of the disclosure will be described.

Various processing is described herein in the context of and/or as beingperformed upon photos. However, the processing as described herein isnot limited to photos. That is, censorship processing, filteredfollowing processing, segmentation processing and other processing asdescribed herein can be applied to any media, which can be described asa “media item” or as “media”, as desired including photos, comments,content, video, sound media, text content, posts and/or other media, forexample.

As described herein, a “user” can include a human user and/or anelectronic user device, such as a cell phone or a smart phone, absentcontext to the contrary. Relatedly, interfacing with a “user”, asdescribed herein, can include interfacing with a human user and/orinterfacing with an electronic user device, such as a cell phone or asmart phone, absent context to the contrary.

Various naming or nomenclature is used herein for purposes ofexplanation and discussion. It is appreciated that such naming ornomenclature, as set forth in this disclosure, can be varied as desired.For example, the particular names of the areas or designations describedherein, such as “local” and “patch” and “spot” can be varied as desired.

Various processing is described herein so as to generate patches andother areas. Once such an area is generated, such area can be designatedas a “spot”, or in some other manner designated with elevated status,once the particular area has attained a certain density of media, forexample. For example, once a patch has attained a predetermined numberof photos, e.g. 10 photos, the patch can be designated as a spot.Various processing can be accorded to such spot, as described herein.Such processing can include providing enhanced user access to suchpatch/spot and the media associated therewith.

As described herein, various processing is described as being performedin the context of a particular “area” or “geographical area”. However,as desired and as suitable, it is appreciated that such processing canalso be applied in other contexts such as a popular location, alandmark, a venue, an attraction, a Zip code, a restaurant, a store,and/or a voting ward, for example. For example, an attraction could belinked or associated with a particular patch (or other area). Picturesor photos associated with such particular patch could effectively be“votes” for such attraction. Different areas, associated with respectiveattractions, could be compared or “voted” on using pictures.

Various processing is described herein as being performed on or withregard to a “spot”, wherein the spot is an area that has a predetermineddensity of photos, for example. Such described processing can beperformed on other areas or points of interest, for example, as may bedesired.

Various processing associated with segmentation of an area and the worldis described herein. It is appreciated that an area may be broken intomultiple areas and may be segmented as desired. The size of the areas,the number of areas in a higher level area (e.g. number of patch areasin local areas) may be varied as desired. Also, the number of levels ofareas can be varied.

As described herein, at least some embodiments of the system of thedisclosure and various processes, of embodiments, are described as beingperformed by one or more computer processors. Such one or more computerprocessors may be in the form of a “processing machine,” i.e. a tangiblyembodied machine or an “apparatus”. As used herein, the term “processingmachine” can be understood to include at least one processor that usesat least one memory. The at least one memory can store a set ofinstructions. The instructions may be either permanently or temporarilystored in the memory or memories of the processing machine. Theprocessor can execute the instructions that are stored in the memory ormemories in order to process data. The set of instructions may includevarious instructions that perform a particular task or tasks, such asany of the processing as described herein. Such a set of instructionsfor performing a particular task may be characterized as a program,software program, code or simply software. Various processing isdescribed herein as performed by a computer processor (CP). Suchcomputer processor can be constituted by or include the processingmachine described herein. Such computer processor (CP) can be describedas a computer processor portion (CPP), a computer processing portion, aprocessor, and/or similar constructs, for example.

As noted above, the processing machine, which may be constituted, forexample, by the particular system and/or systems described above,executes the instructions that are stored in the memory or memories toprocess data. This processing of data may be in response to commands bya user or users of the processing machine, in response to previousprocessing, in response to a request by another processing machineand/or any other input, for example.

As noted above, the machine used to implement the disclosure may be inthe form of a processing machine. The processing machine may alsoutilize (or be in the form of) any of a wide variety of othertechnologies including a special purpose computer, a computer systemincluding a microcomputer, mini-computer or mainframe for example, aprogrammed microprocessor, a micro-controller, a peripheral integratedcircuit element, a CSIC (Consumer Specific Integrated Circuit) or ASIC(Application Specific Integrated Circuit) or other integrated circuit, alogic circuit, a digital signal processor, a programmable logic devicesuch as a FPGA, PLD, PLA or PAL, or any other device or arrangement ofdevices that can be capable of implementing the steps of the processesof the disclosure.

The processing machine used to implement the disclosure may utilize asuitable operating system. Thus, embodiments of the disclosure mayinclude a processing machine running the Windows 10 operating system,the Windows 8 operating system, Microsoft Windows™ Vista™ operatingsystem, the Microsoft Windows™ XP™ operating system, the MicrosoftWindows™ NT™ operating system, the Windows™ 2000 operating system, theUnix operating system, the Linux operating system, the Xenix operatingsystem, the IBM AIX™ operating system, the Hewlett-Packard UX™ operatingsystem, the Novell Netware™ operating system, the Sun MicrosystemsSolaris™ operating system, the OS/2™ operating system, the BeOS™operating system, the Macintosh operating system, the Apache operatingsystem, an OpenStep™ operating system or another operating system orplatform.

It is appreciated that in order to practice the method of the disclosureas described above, it is not necessary that the processors and/or thememories of the processing machine be physically located in the samegeographical place. That is, each of the processors and the memoriesused by the processing machine may be located in geographically distinctlocations and connected so as to communicate in any suitable mannerAdditionally, it is appreciated that each of the processor and/or thememory may be composed of different physical pieces of equipment.Accordingly, it is not necessary that the processor be one single pieceof equipment in one location and that the memory be another single pieceof equipment in another location. That is, it is contemplated that theprocessor may be two pieces of equipment in two different physicallocations. The two distinct pieces of equipment may be connected in anysuitable manner Additionally, the memory may include two or moreportions of memory in two or more physical locations.

To explain further, processing as described above can be performed byvarious components and various memories. However, it is appreciated thatthe processing performed by two distinct components as described abovemay, in accordance with a further embodiment of the disclosure, beperformed by a single component. Further, the processing performed byone distinct component as described above may be performed by twodistinct components. For example, processing as described herein mightbe performed in part by the system 100 or other system or server, inpart by some third party resource 30, and in part by a user device 20,with reference to FIG. 1. In a similar manner, the memory storageperformed by two distinct memory portions as described above may, inaccordance with a further embodiment of the disclosure, be performed bya single memory portion. Further, the memory storage performed by onedistinct memory portion as described above may be performed by twomemory portions.

Further, as also described above, various technologies may be used toprovide communication between the various processors and/or memories, aswell as to allow the processors and/or the memories of the disclosure tocommunicate with any other entity; i.e., so as to obtain furtherinstructions or to access and use remote memory stores, for example.Such technologies used to provide such communication might include anetwork, the Internet, Intranet, Extranet, LAN, an Ethernet, or anyclient server system that provides communication, for example. Suchcommunications technologies may use any suitable protocol such asTCP/IP, UDP, or OSI, for example.

As described above, a set of instructions can be used in the processingof the disclosure on the processing machine, for example. The set ofinstructions may be in the form of a program or software. The softwaremay be in the form of system software or application software, forexample. The software might also be in the form of a collection ofseparate programs, a program module within a larger program, or aportion of a program module, for example. The software used might alsoinclude modular programming in the form of object oriented programming.The software tells the processing machine what to do with the data beingprocessed.

Further, it is appreciated that the instructions or set of instructionsused in the implementation and operation of the disclosure may be in asuitable form such that the processing machine may read theinstructions. For example, the instructions that form a program may bein the form of a suitable programming language, which can be convertedto machine language or object code to allow the processor or processorsto read the instructions. That is, written lines of programming code orsource code, in a particular programming language, can be converted tomachine language using a compiler, assembler or interpreter. The machinelanguage can be binary coded machine instructions that are specific to aparticular type of processing machine, i.e., to a particular type ofcomputer, for example. The computer understands the machine language.

A suitable programming language may be used in accordance with thevarious embodiments of the disclosure. Illustratively, the programminglanguage used may include assembly language, Ada, APL, Basic, C, C++,COBOL, dBase, Forth, Fortran, Java, Modula-2, Pascal, Prolog, REXX,Visual Basic, and/or JavaScript, for example. Further, it is notnecessary that a single type of instructions or single programminglanguage be utilized in conjunction with the operation of the system andmethod of the disclosure. Rather, any number of different programminglanguages may be utilized as can be necessary or desirable.

Also, the instructions and/or data used in the practice of thedisclosure may utilize any compression or encryption technique oralgorithm, as may be desired. An encryption module might be used toencrypt data. Further, files or other data may be decrypted using asuitable decryption module, for example.

As described above, the disclosure may illustratively be embodied in theform of a processing machine, including a computer or computer system,for example, that includes at least one memory. It is to be appreciatedthat the set of instructions, i.e., the software for example, thatenables the computer operating system to perform the operationsdescribed above may be contained on any of a wide variety of media ormedium, as desired. Further, the data that can be processed by the setof instructions might also be contained on any of a wide variety ofmedia or medium. That is, the particular medium, i.e., the memory in theprocessing machine, utilized to hold the set of instructions and/or thedata used in the disclosure may take on any of a variety of physicalforms or transmissions, for example. Illustratively, as also describedabove, the medium may be in the form of paper, paper transparencies, acompact disk, a DVD, an integrated circuit, a hard disk, a floppy disk,an optical disk, a magnetic tape, a RAM, a ROM, a PROM, a EPROM, a wire,a cable, a fiber, communications channel, a satellite transmissions orother remote transmission, as well as any other medium or source of datathat may be read by the processors of the disclosure.

Further, the memory or memories used in the processing machine thatimplements the disclosure may be in any of a wide variety of forms toallow the memory to hold instructions, data, or other information, ascan be desired. Thus, the memory might be in the form of a database tohold data. The database might use any desired arrangement of files suchas a flat file arrangement or a relational database arrangement, forexample.

In the system and method of the disclosure, a variety of “userinterfaces” may be utilized to allow a user to interface with theprocessing machine or machines that are used to implement thedisclosure. As used herein, a user interface includes any hardware,software, or combination of hardware and software used by the processingmachine that allows a user to interact with the processing machine. Auser interface may be in the form of a dialogue screen for example. Auser interface may also include any of a mouse, touch screen, keyboard,voice reader, voice recognizer, dialogue screen, menu box, list,checkbox, toggle switch, a pushbutton or any other device that allows auser to receive information regarding the operation of the processingmachine as it processes a set of instructions and/or provide theprocessing machine with information. Accordingly, the user interface canbe any device that provides communication between a user and aprocessing machine. The information provided by the user to theprocessing machine through the user interface may be in the form of acommand, a selection of data, or some other input, for example.

As discussed above, a user interface can be utilized by the processingmachine that performs a set of instructions such that the processingmachine processes data for a user. The user interface can be typicallyused by the processing machine for interacting with a user either toconvey information or receive information from the user. However, itshould be appreciated that in accordance with some embodiments of thesystem and method of the disclosure, it is not necessary that a humanuser actually interact with a user interface used by the processingmachine of the disclosure. Rather, it is also contemplated that the userinterface of the disclosure might interact, i.e., convey and receiveinformation, with another processing machine, rather than a human user.Accordingly, the other processing machine might be characterized as auser. Further, it is contemplated that a user interface utilized in thesystem and method of the disclosure may interact partially with anotherprocessing machine or processing machines, while also interactingpartially with a human user.

In this disclosure, quotation marks, such as with the language “spot”,have been used to enhance readability and/or to parse out a term orphrase for clarity.

It will be appreciated that features, elements and/or characteristicsdescribed with respect to one embodiment of the disclosure may bevariously used with other embodiments of the disclosure as may bedesired.

It will be appreciated that the effects of the present disclosure arenot limited to the above-mentioned effects, and other effects, which arenot mentioned herein, will be apparent to those in the art from thedisclosure and accompanying claims.

Although the preferred embodiments of the present disclosure have beendisclosed for illustrative purposes, those skilled in the art willappreciate that various modifications, additions and substitutions arepossible, without departing from the scope and spirit of the disclosureand accompanying claims.

As used herein, the term “and/or” includes any and all combinations ofone or more of the associated listed items.

It will be understood that, although the terms first, second, third,etc., may be used herein to describe various elements, components,regions, layers and/or sections, these elements, components, regions,layers and/or sections should not be limited by these terms. These termsare only used to distinguish one element, component, process step,region, layer or section from another region, layer or section. Thus, afirst element, component, process step, region, layer or section couldbe termed a second element, component, process step, region, layer orsection without departing from the teachings of the present disclosure.

Spatially and organizationally relative terms, such as “lower”, “upper”,“top”, “bottom”, “left”, “right”, “north”, “south”, “east”, “west”,“up”, “down”, “right”, “left”, “upper threshold”, “lower threshold” andthe like, may be used herein for ease of description to describe therelationship of one element or feature to another element(s) orfeature(s) as illustrated in the drawing figures. It will be understoodthat spatially and organizationally relative terms are intended toencompass different orientations of or organizational aspects ofcomponents in use or in operation, in addition to the orientation orparticular organization depicted in the drawing figures.

The terminology used herein is for the purpose of describing particularembodiments only and is not intended to be limiting of the disclosure.As used herein, the singular forms “a”, “an” and “the” are intended toinclude the plural forms as well, unless the context clearly indicatesotherwise.

It will be further understood that the terms “comprises” and/or“comprising,” when used in this specification, specify the presence ofstated features, integers, process steps, operations, elements, and/orcomponents, but do not preclude the presence or addition of one or moreother features, integers, process steps, operations, elements,components, and/or groups thereof.

Embodiments of the disclosure are described herein with reference todiagrams, flowcharts and/or other illustrations, for example, that areschematic illustrations of idealized embodiments (and intermediatecomponents) of the disclosure. As such, variations from theillustrations are to be expected. Thus, embodiments of the disclosureshould not be construed as limited to the particular organizationaldepiction of components and/or processing illustrated herein but are toinclude deviations in organization of components and/or processing.

Unless otherwise defined, all terms (including technical and scientificterms) used herein have the same meaning as commonly understood by oneof ordinary skill in the art to which this disclosure belongs. It willbe further understood that terms, such as those defined in commonly useddictionaries, should be interpreted as having a meaning that isconsistent with their meaning in the context of the relevant art andwill not be interpreted in an idealized or overly formal sense unlessexpressly so defined herein.

Any reference in this specification to “one embodiment,” “anembodiment,” “example embodiment,” etc., means that a particularfeature, structure, or characteristic described in connection with theembodiment is included in at least one embodiment of the disclosure. Theappearances of such phrases in various places in the specification arenot necessarily all referring to the same embodiment. Further, asotherwise noted herein, when a particular feature, structure, orcharacteristic is described in connection with any embodiment, it issubmitted that it is within the purview of one skilled in the art toeffect and/or use such feature, structure, or characteristic inconnection with other ones of the embodiments.

While the subject matter has been described in detail with reference toexemplary embodiments thereof, it will be apparent to one skilled in theart that various changes can be made, and equivalents employed, withoutdeparting from the scope of the disclosure.

All references and/or documents referenced herein are herebyincorporated by reference in their entirety. It will be readilyunderstood by those persons skilled in the art that the presentdisclosure is susceptible to broad utility and application. Manyembodiments and adaptations of the present disclosure other than thoseherein described, as well as many variations, modifications andequivalent arrangements, will be apparent from or reasonably suggestedby the present disclosure and foregoing description thereof, withoutdeparting from the substance or scope of the disclosure.

Accordingly, while the present disclosure has been described here indetail in relation to its exemplary embodiments, it is to be understoodthat this disclosure is only illustrative and exemplary of the presentdisclosure and is made to provide an enabling disclosure of thedisclosure. Accordingly, the foregoing disclosure is not intended to beconstrued or to limit the present disclosure or otherwise to exclude anyother such embodiments, adaptations, variations, modifications andequivalent arrangements.

What is claimed is:
 1. An apparatus to process digital photos, theapparatus including a tangibly embodied computer processor (CP) and atangibly embodied database, the CP implementing instructions on anon-transitory computer medium disposed in the database, and thedatabase in communication with the CP, the apparatus comprising: acommunication portion for providing communication between the CP and aplurality of user devices; the database that includes the non-transitorycomputer medium, and the database including the instructions and aframework for storing a collection of photos, and the CP, and the CPperforming processing including: storing the collection of photos, andeach photo, in the collection of photos, including (a) image data and(b) metadata; interfacing with one or more first users to identify afirst association between the one or more first users and respectivephotos in a first collection of photos, and the first collection ofphotos constituting a first filtered photo set of photos; interfacingwith one or more second users to identify a second association betweenthe one or more second users and respective photos in a secondcollection of photos, and the second collection of photos constituting asecond filtered photo set of photos; and interfacing with a third userto allow the third user to select the one or more first users, so as toview the first filtered photo set; interfacing with the third user toallow the third user to select the one or more second users, so as toview the second filtered photo set; whereby the third user is providedwith access to different filtered photo sets that are representative of(a) a one or more first users perspective of the one or more first usersas represented by the first filtered photo set, and (b) a one or moresecond users perspective of the one or more second users as representedby the second filtered photo set; and the one or more first users, theone or more second users, and the third user each include a respectiveuser device; and the first and second collection of photos is of thecollection of photos.
 2. The apparatus of claim 1, the first associationis constituted by that the one or more first users took each of thephotos in the first collection of photos; and the second association isconstituted by that the one or more second users took each of the photosin the second collection of photos.
 3. The apparatus of claim 2, thefirst filtered photo set and the second filtered photo set are from asame geographical area.
 4. The apparatus of claim 1, the firstassociation is constituted by that the one or more first users likedeach of the photos in the first collection of photos; and the secondassociation is constituted by that the one or more second users likedeach of the photos in the second collection of photos.
 5. The apparatusof claim 4, the first filtered photo set and the second filtered photoset are from a same geographical area.
 6. The apparatus of claim 1, thefirst association is constituted by a user tag associated with the oneor more first users being determined to match a respective photo tagassociated with each of the photos in the first collection of photos. 7.The apparatus of claim 6, the photo tag represents a group to whichphotos in the first filtered photo set are associated, and the user tagprovides an association between the one or more first users and thegroup.
 8. The apparatus of claim 7, the group of users is in the form ofan affinity group that represents an affinity to particular subjectmatter.
 9. The apparatus of claim 7, the group is in the form of afriends group that represents a group of friends.
 10. The apparatus ofclaim 6, the photo tag designates a preference, and the user tagrepresents such same preference, such that the photo tag and the usertag are deemed to match.
 11. The apparatus of claim 6, each photo tagrepresents a geographical location.
 12. The apparatus of claim 6, eachphoto tag represents an attribute of the photo, and the attributeincluding at least one selected from the group consisting of lens type,time of day, location, scene type, and season of the year.
 13. Theapparatus of claim 1, the CP performing processing includes: (a)determining that a first photo (a) is in the first filtered photo set ofphotos and (b) IS in the second filtered photo set of photos; (b)determining that a second photo (a) is in the first filtered photo setof photos and (b) IS NOT in the second filtered photo set of photos; (c)deeming that a following strength of the first photo is greater that afollowing strength of the second photo based on (a) and (b).
 14. Theapparatus of claim 1, the first filtered photo set and the secondfiltered photo set are from a first geographical area; and the thirduser being provided with access to the first filtered photo set and thesecond filtered photo allows the user to perform validation ofinformation regarding the first geographical area.
 15. The apparatus ofclaim 14, the validation of information regarding the first geographicalarea relates to popularity of the first geographical area.
 16. Theapparatus of claim 1, the one or more first users is a single user, andthe one or more second users is a further single user.
 17. An apparatusto process digital photos, the apparatus including a tangibly embodiedcomputer processor (CP) and a tangibly embodied database, the CPimplementing instructions on a non-transitory computer medium disposedin the database, and the database in communication with the CP, theapparatus comprising: a communication portion for providingcommunication between the CP and a plurality of user devices; thedatabase that includes the non-transitory computer medium, and thedatabase including the instructions and a framework for storing acollection of photos, and the CP, and the CP performing processingincluding: storing the collection of photos, and each photo, in thecollection of photos, including (a) image data and (b) metadata;interfacing with one or more first users to identify a first associationbetween the one or more first users and respective photos in a firstcollection of photos, and the first collection of photos constituting afirst filtered photo set of photos; identifying a second collection ofphotos that have been input into the system, and the second collectionof photos constituting a second filtered photo set of photos; andinterfacing with a third user to allow the third user to select the oneor more first users, so as to view the first filtered photo set;interfacing with the third user to allow the third user to view thesecond filtered photo set; whereby the third user is provided withaccess to different filtered photo sets that are representative of (a) aone or more first users perspective of the one or more first users asrepresented by the first filtered photo set, and (b) a one or moresecond users perspective of one or more second users as represented bythe second filtered photo set; and the one or more first users, the oneor more second users, and the third user each include a respective userdevice; and the first and second collection of photos is of thecollection of photos.
 18. The apparatus of claim 17, the secondcollection of photos is constituted by one of: (a) photos, which possessa first attribute, (b) photos, which possess a second attribute, thatare accessible by the third user, and (c) photos, which possess a thirdattribute, that are accessible by the third user, and wherein: the firstattribute is accessibility by the third user; the second attributereflects that each photo, in the second collection of photos, were eachtaken in a same geographical area, and the third attribute reflects thateach photo, in the second collection of photos, were each taken by asame user; and wherein, the one or more first users includes at leastone selected from the group consisting of: an individual, group ofusers, trusted critics group, an affinity group, followed users,friends, groups of friends, trusted specialty groups, persons, andgroups.
 19. An apparatus to process digital media, the apparatusincluding a tangibly embodied computer processor (CP) and a tangiblyembodied database, the CP implementing instructions on a non-transitorycomputer medium disposed in the database, and the database incommunication with the CP, the apparatus comprising: a communicationportion for providing communication between the CP and a plurality ofuser devices; the database that includes the non-transitory computermedium, and the database including the instructions and a framework forstoring a collection of media, and the CP, and the CP performingprocessing including: storing the collection of media, and each media,in the collection of media, including (a) content data and (b) metadata;interfacing with one or more first users to identify a first associationbetween the one or more first users and respective media in a firstcollection of media, and the first collection of media constituting afirst filtered media set of media; identifying a second collection ofmedia that have been input into the system, and the second collection ofmedia constituting a second filtered media set of media; and interfacingwith a third user to allow the third user to select the one or morefirst users, so as to view the first filtered media set; interfacingwith the third user to allow the third user to view the second filteredmedia set; whereby the third user is provided with access to differentfiltered media sets that are representative of (a) a one or more firstusers perspective of the one or more first users as represented by thefirst filtered media set, and (b) a one or more second users perspectiveof one or more second users as represented by the second filtered mediaset; and the one or more first users, the one or more second users, andthe third user each include a respective user device; and the first andsecond collection of media is of the collection of media.
 20. Theapparatus of claim 19, the media includes photos, and the content datafor each photo includes data representing a photograph.